19.3.4.12 Background Detection, Background Model

Scene Background Initialization (SBI) Dataset,
2016
HTML Version. Dataset, Background. 1603
14 sequences with ground truth.
See also Towards Benchmarking Scene Background Initialization.

Mukawa, N., Kuroda, H.,
Uncovered Background Prediction in Interframe Coding,
Commun(33), 1985, pp. 1227-1231.
See also Interframe Coding System for Video Teleconferencing Signal Transmission at a 1.5 Mbit/S Rate, An. BibRef 8500

Morton, R.R.A.[Roger R. A.], Lewis, S.[Scott],
Forward look ahead techniques for tracking background and noise levels in scanned video images,
US_Patent4,853,795, Aug 1, 1989
WWW Link. BibRef 8908

Long, W., Yang, Y.H.,
Stationary Background Generation: An Alternative to the Difference of Two Images,
PR(23), No. 12, 1990, pp. 1351-1359.
Elsevier DOI BibRef 9000

Yang, Y.H., Levine, M.D.,
The Background Primal Sketch: An Approach for Tracking Moving Objects,
MVA(5), 1992, pp. 17-34. BibRef 9200

Lettera, C., Masera, L.,
Foreground/background segmentation in videotelephony,
SP:IC(1), No. 2, October 1990, pp. 181-189.
Elsevier DOI 0001
BibRef

Thoma, R.[Robert], Bierling, M.[Matthias],
Motion compensating interpolation considering covered and uncovered background,
SP:IC(1), No. 2, October 1990, pp. 191-212.
Elsevier DOI 0001
Motion compensating interpolation, digital television sequences, low bit rate codec, hierarchical blockmatching, change detection, segmentation BibRef

Elnagar, A.[Ashraf], Basu, A.[Anup], Elnagar, A., Basu, A.,
Motion Detection Using Background Constraints,
PR(28), No. 10, October 1995, pp. 1537-1554.
Elsevier DOI BibRef 9510

Khosravi, M.[Mehdi], Moed, M.C.[Michael C.], Crabtree, R.N.[Ralph N.], Perez-Jacome, J.E.[Jorge E.],
System and method for multi-resolution background adaptation,
US_Patent6,061,088, May 9, 2000
WWW Link. BibRef 0005

Crabtree, R.N.[Ralph N.], Moed, M.C.[Michael C.], Khosravi, M.[Mehdi],
System and method for matching image information to object model information,
US_Patent6,185,314, Feb 6, 2001
WWW Link. BibRef 0102
And:
System and method for tracking movement of objects in a scene using correspondence graphs,
US_Patent6,295,367, Sep 25, 2001
WWW Link. BibRef

Durucan, E., Ebrahimi, T.,
Change detection and background extraction by linear algebra,
PIEEE(89), No. 10, October 2001, pp. 1368-1381.
IEEE DOI BibRef 0110

Durucan, E., Ebrahimi, T.,
Moving object detection between multiple and color images,
AVSBS03(243-251).
IEEE DOI 0310
BibRef

Durucan, E., Snoeckx, J., Weilenmann, Y.,
Illumination invariant background extraction,
CIAP99(1136-1139).
IEEE DOI 9909
BibRef

Cavallaro, A., and Ebrahimi, T.,
Accurate video object segmentation through change detection,
ICME02(I: 445-448). BibRef 0200

Herrero-Jaraba, E.[Elías], Orrite-Uruñuela, C.[Carlos], Senar, J.[Jesús],
Detected motion classification with a double-background and a Neighborhood-based difference,
PRL(24), No. 12, August 2003, pp. 2079-2092.
Elsevier DOI 0304
BibRef

Lipton, A.J.[Alan J.], Allmen, M.C.[Mark C.], Haering, N.C.[Niels C.], Severson, W.[William], Strat, T.M.[Thomas M.],
Video segmentation using statistical pixel modeling,
US_Patent6,625,310, Sep 23, 2003
WWW Link. BibRef 0309
And: US_Patent7,224,852, May 29, 2007
WWW Link. Foreground and background detection. BibRef

Lipton, A.J.[Alan J.], Haering, N.C.[Niels C.], Allmen, M.C.[Mark C.], Venetianer, P.L.[Peter L.], Slowe, T.E.[Thomas E.], Zhang, Z.[Zhong],
Video scene background maintenance using statistical pixel modeling,
US_Patent6,987,883, Jan 17, 2006
WWW Link. BibRef 0601

Lee, C.N.[Cheoung N.], Samaddar, S.[Sumitro],
Background recovery in monocular vision,
US_Patent5,684,887, Nov 4, 1997
WWW Link. BibRef 9711

Mertens, M.J.W.[Mark Jozef Willem], de Haan, G.[Gerard],
Foreground/background detector,
US_Patent6,771,799, Aug 3, 2004
WWW Link. BibRef 0408

Colombari, A.[Andrea], Fusiello, A.[Andrea], Murino, V.[Vittorio],
Segmentation and tracking of multiple video objects,
PR(40), No. 4, April 2007, pp. 1307-1317.
Elsevier DOI 0701
BibRef
And:
Video Objects Segmentation by Robust Background Modeling,
CIAP07(155-164).
IEEE DOI 0709
BibRef
Earlier:
Background Initialization in Cluttered Sequences,
PercOrg06(197).
IEEE DOI 0609
Content-based representation, MPEG, Video coding, Video sequence analysis; Mosaicing, Motion segmentation BibRef

Colombari, A.[Andrea], Cristani, M.[Marco], Murino, V.[Vittorio], Fusiello, A.[Andrea],
Exemplar-based background model initialization,
VSSN05(29-36).
WWW Link. 0511
BibRef

Colombari, A.[Andrea], Fusiello, A.[Andrea],
Patch-Based Background Initialization in Heavily Cluttered Video,
IP(19), No. 4, April 2010, pp. 926-933.
IEEE DOI 1003
BibRef

Yalcin, H.[Hulya], Collins, R.[Robert], Hebert, M.[Martial],
Background Estimation under Rapid Gain Change in Thermal Imagery,
CVIU(106), No. 2-3, May-June 2007, pp. 148-161.
Elsevier DOI 0705
BibRef
Earlier: OTCBVS05(III: 12-12).
IEEE DOI 0507
Automatic gain control, Thermal sensors, Airborne video imagery Moving ground vehicles. BibRef

Wang, W.Q.[Wei-Qiang], Yang, J.[Jie], Gao, W.[Wen],
Modeling Background and Segmenting Moving Objects from Compressed Video,
CirSysVideo(18), No. 5, May 2008, pp. 670-681.
IEEE DOI 0711
BibRef

Wang, W.Q.[Wei-Qiang], Chen, D.T.[Da-Tong], Gao, W.[Wen], Yang, J.[Jie],
Modeling background from compressed video,
PETS05(161-168).
IEEE DOI 0602
BibRef

Ren, Y.[Ying], Chua, C.S.[Chin Seng], Ho, Y.K.[Yeong Khing],
Motion Detection From Time-varied Background,
IJIG(2), No. 2, April 2002, pp. 163-178. 0204
BibRef

Buehler, C.J.[Christopher J.],
Method and apparatus for computerized image background analysis,
US_Patent7,221,775, May 22, 2007
WWW Link. BibRef 0705
And:
Method of counting objects in a monitored environment and apparatus for the same,
US_Patent7,346,187, Mar 18, 2008
WWW Link. BibRef
And: US_Patent7,394,852, Jul 1, 2008
WWW Link. BibRef

Tavakkoli, A.[Alireza], Nicolescu, M.[Mircea], Bebis, G.N.[George N.], Nicolescu, M.[Monica],
Non-parametric statistical background modeling for efficient foreground region detection,
MVA(20), No. 6, October 2009, pp. xx-yy.
Springer DOI 0910
BibRef
Earlier:
Efficient background modeling through incremental Support Vector Data Description,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Porr, W.[William], Easton, J.[James], Tavakkoli, A.[Alireza], Loffredo, D.[Donald], Simmons, S.[Sean],
Accurate and Efficient Non-Parametric Background Detection for Video Surveillance,
ISVC18(93-105).
Springer DOI 1811
BibRef

Wilson, B.[Brandon], Tavakkoli, A.[Alireza],
An Efficient Non-parametric Background Modeling Technique with CUDA Heterogeneous Parallel Architecture,
ISVC15(I: 210-220).
Springer DOI 1601
BibRef

Tavakkoli, A.[Alireza], Ambardekar, A.[Amol], Nicolescu, M.[Mircea], Louis, S.[Sushil],
A Genetic Approach to Training Support Vector Data Descriptors for Background Modeling in Video Data,
ISVC07(II: 318-327).
Springer DOI 0711
BibRef

Tavakkoli, A.[Alireza], Nicolescu, M.[Mircea], Bebis, G.N.[George N.],
A Novelty Detection Approach for Foreground Region Detection in Videos with Quasi-stationary Backgrounds,
ISVC06(I: 40-49).
Springer DOI 0611
BibRef
And:
Automatic Statistical Object Detection for Visual Surveillance,
Southwest06(144-148).
IEEE DOI 0603
BibRef
And:
Robust Recursive Learning for Foreground Region Detection in Videos with Quasi-Stationary Backgrounds,
ICPR06(I: 315-318).
IEEE DOI 0609
BibRef
Earlier:
Automatic Robust Background Modeling Using Multivariate Non-parametric Kernel Density Estimation for Visual Surveillance,
ISVC05(363-370).
Springer DOI 0512
BibRef

Chiu, C.C., Ku, M.Y., Liang, L.W.,
A Robust Object Segmentation System Using a Probability-Based Background Extraction Algorithm,
CirSysVideo(20), No. 4, April 2010, pp. 518-528.
IEEE DOI 1003
BibRef

Tzevanidis, K.[Konstantinos], Argyros, A.[Antonis],
Unsupervised learning of background modeling parameters in multicamera systems,
CVIU(115), No. 1, January 2011, pp. 105-116.
Elsevier DOI 1011
Background modeling, Foreground detection, Multicamera consensus; Particle Swarm Optimization, Camera networks BibRef

Reddy, V.[Vikas], Sanderson, C.[Conrad], Lovell, B.C.[Brian C.],
A Low-Complexity Algorithm for Static Background Estimation from Cluttered Image Sequences in Surveillance Contexts,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1101
BibRef
Earlier:
Robust Foreground Object Segmentation via Adaptive Region-Based Background Modelling,
ICPR10(3939-3942).
IEEE DOI 1008
BibRef

Reddy, V.[Vikas], Sanderson, C.[Conrad], Lovell, B.C.[Brian C.],
Improved Foreground Detection via Block-Based Classifier Cascade With Probabilistic Decision Integration,
CirSysVideo(23), No. 1, January 2013, pp. 83-93.
IEEE DOI 1302
BibRef

Reddy, V.[Vikas], Sanderson, C.[Conrad], Sanin, A.[Andres], Lovell, B.C.[Brian C.],
MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos,
ACCV10(III: 547-559).
Springer DOI 1011
BibRef
Earlier:
Adaptive Patch-Based Background Modelling for Improved Foreground Object Segmentation and Tracking,
AVSS10(172-179).
IEEE DOI 1009
BibRef

Valentine, B.[Brian], Apewokin, S.[Senyo], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott],
An efficient, chromatic clustering-based background model for embedded vision platforms,
CVIU(114), No. 11, November 2010, pp. 1152-1163.
Elsevier DOI 1011
Background modeling, Multimodal, Embedded computing BibRef

Azmat, S.[Shoaib], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott],
Spatio-temporal multimodal mean,
Southwest14(81-84)
IEEE DOI 1406
BibRef
Earlier:
Temporal multi-modal mean,
Southwest12(73-76).
IEEE DOI 1205
data visualisation. Background/foreground classification in motion BibRef

Valentine, B.[Brian], Choi, J.[Jee], Apewokin, S.[Senyo], Wills, L.M.[Linda M.], Wills, J.S.[J. Scott],
Bypassing BigBackground: An efficient hybrid background modeling algorithm for embedded video surveillance,
ICDSC08(1-8).
IEEE DOI 0809
BibRef

Valentine, B.[Brian], Apewokin, S.[Senyo], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott], Gentile, A.,
Midground object detection in real world video scenes,
AVSBS07(517-522).
IEEE DOI 0709
BibRef
And: A2, A1, A3, A4, A5:
Multimodal Mean Adaptive Backgrounding for Embedded Real-Time Video Surveillance,
EmbedCV07(1-6).
IEEE DOI 0706
BibRef

Bales, M.R.[M. Ryan], Forsthoefel, D.[Dana], Valentine, B.[Brian], Wills, D.S.[D. Scott], Wills, L.M.[Linda M.],
BigBackground-Based Illumination Compensation for Surveillance Video,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1101
BibRef
And: A1, A2, A4, A5, Only:
Illumination change compensation techniques to improve kinematic tracking,
WACV11(434-439).
IEEE DOI 1101
BibRef
Earlier: A1, A2, A4, A5, Only:
Chromatic Sensitivity of Illumination Change Compensation Techniques,
ISVC10(I: 211-220).
Springer DOI 1011
BibRef

Yamamoto, A.[Ayaka], Iwai, Y.[Yoshio], Ishiguro, H.[Hiroshi],
Real-Time Object Detection Using Adaptive Background Model and Margined Sign Correlation,
IEICE(E94-D), No. 2, February 2011, pp. 325-335.
WWW Link. 1102
BibRef
Earlier: A1, A2, Only:
Real-Time Object Detection with Adaptive Background Model and Margined Sign Correlation,
ACCV09(III: 65-74).
Springer DOI 0909
BibRef

Yoshimura, H.[Hironori], Iwai, Y.[Yoshio], Yachida, M.[Masahiko],
Object Detection with Adaptive Background Model and Margined Sign Cross Correlation,
ICPR06(III: 19-23).
IEEE DOI 0609
BibRef

Evangelio, R.H.[Rubén Heras], Sikora, T.[Thomas],
Static Object Detection Based on a Dual Background Model and a Finite-State Machine,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103

See also system for automatic and interactive detection of static objects, A. BibRef

Evangelio, R.H.[Rubén Heras], Sikora, T.[Thomas],
Complementary background models for the detection of static and moving objects in crowded environments,
AVSBS11(71-76).
IEEE DOI 1111
BibRef

Suhr, J.K., Jung, H.G., Li, G., Noh, S.I., Kim, J.,
Background Compensation for Pan-Tilt-Zoom Cameras Using 1-D Feature Matching and Outlier Rejection,
CirSysVideo(21), No. 3, March 2011, pp. 371-377.
IEEE DOI 1104
BibRef

Lopez-Rubio, E.[Ezequiel], Luque-Baena, R.M.[Rafael Marcos],
Stochastic approximation for background modelling,
CVIU(115), No. 6, June 2011, pp. 735-749.
Elsevier DOI 1104
Background modelling, Probabilistic mixture models, Stochastic approximation, Unsupervised learning BibRef

López-Rubio, F.J.[Francisco Javier], López-Rubio, E.[Ezequiel],
Features for stochastic approximation based foreground detection,
CVIU(133), No. 1, 2015, pp. 30-50.
Elsevier DOI 1502
Background modeling BibRef

López-Rubio, F.J.[Francisco Javier], López-Rubio, E.[Ezequiel],
Local color transformation analysis for sudden illumination change detection,
IVC(37), No. 1, 2015, pp. 31-47.
Elsevier DOI 1505
Background modeling BibRef

Zhao, Y.D.[You-Dong], Gong, H.F.[Hai-Feng], Jia, Y.D.[Yun-De], Zhu, S.C.[Song-Chun],
Background modeling by subspace learning on spatio-temporal patches,
PRL(33), No. 9, 1 July 2012, pp. 1134-1147.
Elsevier DOI 1202
Visual surveillance, Background modeling, Spatio-temporal patch; Subspace learning BibRef

Zhao, Y.D.[You-Dong], Gong, H.F.[Hai-Feng], Lin, L.[Liang], Jia, Y.D.[Yun-De],
Spatio-temporal patches for night background modeling by subspace learning,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Wang, Y., Liang, Y., Zhang, L., Pan, Q.,
Adaptive spatiotemporal background modelling,
IET-CV(6), No. 5, 2012, pp. 451-458.
DOI Link 1210
BibRef

Cuevas, C.[Carlos], Garcia, N.[Narciso],
Efficient Moving Object Detection for Lightweight Applications on Smart Cameras,
CirSysVideo(23), No. 1, January 2013, pp. 1-14.
IEEE DOI 1302
BibRef
Earlier:
Automatic bandwidth estimation strategy for high-quality non-parametric modeling based moving object detection,
ICIP11(1757-1760).
IEEE DOI 1201
BibRef
Earlier:
Tracking-based non-parametric background-foreground classification in a chromaticity-gradient space,
ICIP10(845-848).
IEEE DOI 1009
BibRef

Cuevas, C.[Carlos], García, N.[Narciso],
Improved background modeling for real-time spatio-temporal non-parametric moving object detection strategies,
IVC(31), No. 9, 2013, pp. 616-630.
Elsevier DOI 1307
Dynamic bandwidth estimation BibRef

Cuevas, C.[Carlos], Mohedano, R.[Raul], Garcia, N.[Narciso],
Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling,
ICIP12(313-316).
IEEE DOI 1302
BibRef

Tsai, T.H.[Tsung-Han], Lin, C.Y.[Chung-Yuan], Li, S.Y.,
Algorithm and Architecture Design of Human-Machine Interaction in Foreground Object Detection With Dynamic Scene,
CirSysVideo(23), No. 1, January 2013, pp. 15-29.
IEEE DOI 1302
BibRef

Peng, D.Z.[De-Zhang], Lin, C.Y.[Chung-Yuan], Sheu, W.T.[Wen-Tsai], Tsai, T.H.[Tsung-Han],
Architecture design for a low-cost and low-complexity foreground object segmentation with Multi-model Background Maintenance algorithm,
ICIP09(3241-3244).
IEEE DOI 0911
BibRef

Park, D.Y.[Dae-Yong], Byun, H.R.[Hye-Ran],
A unified approach to background adaptation and initialization in public scenes,
PR(46), No. 7, July 2013, pp. 1985-1997.
Elsevier DOI 1303
Foreground detection, Background maintenance, Selective learning; Background initialization, Stationary foreground detection, Energy minimization, Public scenes, Visual surveillance BibRef

Hsiao, H.H.[Han-Hui], Leou, J.J.[Jin-Jang],
Background initialization and foreground segmentation for bootstrapping video sequences,
JIVP(2013), No. 1, 2013, pp. xx-yy.
DOI Link 1303
BibRef

Golikov, V., Lebedeva, O.,
Adaptive Detection of Subpixel Targets With Hypothesis Dependent Background Power,
SPLetters(20), No. 8, 2013, pp. 751-754.
IEEE DOI 1307
Gaussian processes BibRef

Kryjak, T.[Tomasz], Komorkiewicz, M.[Mateusz], Gorgon, M.[Marek],
Real-time background generation and foreground object segmentation for high-definition colour video stream in FPGA device,
RealTimeIP(9), No. 1, March 2014, pp. 61-77.
WWW Link. 1403
BibRef

Azmat, S.[Shoaib], Wills, L.M.[Linda M.], Wills, D.S.[D. Scott],
Multilayer background modeling under occlusions,
MVA(25), No. 6, 2014, pp. 1399-1409.
WWW Link. 1408
BibRef

Mould, N.[Nick], Havlicek, J.P.[Joseph P.],
Neighborhood-level learning techniques for nonparametric scene models,
SIViP(8), No. 6, September 2014, pp. 1015-1029.
WWW Link. 1408
BibRef
Earlier:
A stochastic learning algorithm for pixel-level background models,
ICIP12(1233-1236).
IEEE DOI 1302
BibRef

Chiu, W.Y.[Wei-Yao], Tsai, D.M.[Du-Ming],
Dual-mode detection for foreground segmentation in low-contrast video images,
RealTimeIP(9), No. 4, December 2014, pp. 647-659.
Springer DOI 1411
Foreground in surveillance with stationary camera. BibRef

Chen, Y.S.[Yi-Song], Chan, A.B.,
Enhanced Figure-Ground Classification With Background Prior Propagation,
IP(24), No. 3, March 2015, pp. 873-885.
IEEE DOI 1502
feature extraction BibRef

Liu, N.[Ning], Wu, H.[Hefeng], Lin, L.[Liang],
Hierarchical Ensemble of Background Models for PTZ-Based Video Surveillance,
Cyber(45), No. 1, January 2015, pp. 89-102.
IEEE DOI 1502
feature extraction BibRef

Yin, B.C.[Bao-Cai], Zhang, J.[Jing], Wang, Z.F.[Zeng-Fu],
Background segmentation of dynamic scenes based on dual model,
IET-CV(8), No. 6, 2014, pp. 545-555.
DOI Link 1502
image segmentation BibRef

Wang, C.[Chong], Huang, K.Q.[Kai-Qi], Ren, W.Q.[Wei-Qiang], Zhang, J.G.[Jun-Ge], Maybank, S.J.[Steve J.],
Large-Scale Weakly Supervised Object Localization via Latent Category Learning,
IP(24), No. 4, April 2015, pp. 1371-1385.
IEEE DOI 1503
Feature extraction BibRef

Ren, W.Q.[Wei-Qiang], Huang, K.Q.[Kai-Qi], Tao, D., Tan, T.N.[Tie-Niu],
Weakly Supervised Large Scale Object Localization with Multiple Instance Learning and Bag Splitting,
PAMI(38), No. 2, February 2016, pp. 405-416.
IEEE DOI 1601
Bismuth BibRef

Wang, C.[Chong], Ren, W.Q.[Wei-Qiang], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Weakly Supervised Object Localization with Latent Category Learning,
ECCV14(VI: 431-445).
Springer DOI 1408
Know the background, easier to get object. BibRef

Zhang, F., Yang, J., Tai, Y., Tang, J.,
Double Nuclear Norm-Based Matrix Decomposition for Occluded Image Recovery and Background Modeling,
IP(24), No. 6, June 2015, pp. 1956-1966.
IEEE DOI 1504
Gaussian distribution BibRef

Yang, M., Huang, C., Liu, W., Lin, S., Chuang, K.,
Binary Descriptor Based Nonparametric Background Modeling for Foreground Extraction by Using Detection Theory,
CirSysVideo(25), No. 4, April 2015, pp. 595-608.
IEEE DOI 1504
Computational modeling BibRef

Liu, W.[Wei], Yu, H.F.[Hong-Fei], Yuan, H.[Huai], Zhao, H.[Hong], Xu, X.W.[Xiao-Wei],
Effective background modelling and subtraction approach for moving object detection,
IET-CV(9), No. 1, 2015, pp. 13-24.
DOI Link 1504
image motion analysis BibRef

Stagliano, A., Noceti, N., Verri, A., Odone, F.,
Online Space-Variant Background Modeling With Sparse Coding,
IP(24), No. 8, August 2015, pp. 2415-2428.
IEEE DOI 1505
Adaptation models BibRef

Schönborn, S.[Sandro], Egger, B.[Bernhard], Forster, A.[Andreas], Vetter, T.[Thomas],
Background modeling for generative image models,
CVIU(136), No. 1, 2015, pp. 117-127.
Elsevier DOI 1506
Generative models BibRef

Zhao, Z., Zhang, X., Fang, Y.,
Stacked Multilayer Self-Organizing Map for Background Modeling,
IP(24), No. 9, September 2015, pp. 2841-2850.
IEEE DOI 1506
Adaptation models BibRef

Ye, X.C.[Xin-Chen], Yang, J.Y.[Jing-Yu], Sun, X.[Xin], Li, K.[Kun], Hou, C., Wang, Y.,
Foreground-Background Separation From Video Clips via Motion-Assisted Matrix Restoration,
CirSysVideo(25), No. 11, November 2015, pp. 1721-1734.
IEEE DOI 1511
BibRef
Earlier: A2, A3, A1, A4, Only:
Background extraction from video sequences via motion-assisted matrix completion,
ICIP14(2437-2441)
IEEE DOI 1502
Adaptation models. Data mining BibRef

Yang, J.R.[Jiao-Ru], Yang, J.Y.[Jing-Yu], Yang, X.M.[Xue-Meng], Yue, H.J.[Huan-Jing],
Background recovery from video sequences via online motion-assisted RPCA,
VCIP16(1-4)
IEEE DOI 1701
Optimization
See also Landmark Image Super-Resolution by Retrieving Web Images. BibRef

Chacon-Murguia, M.I.[Mario I.], Ramirez-Quintana, J.[Juan], Urias-Zavala, D.[David],
Segmentation of video background regions based on a DTCNN-clustering approach,
SIViP(9), No. 1 Supp, December 2015, pp. 135-144.
Springer DOI 1601
BibRef

Álvarez-Meza, A.M.[Andres M.], Molina-Giraldo, S., Castellanos-Dominguez, G.[German],
Background modeling using Object-based Selective Updating and Correntropy adaptation,
IVC(45), No. 1, 2016, pp. 22-36.
Elsevier DOI 1601
Background modeling BibRef

Pulgarin-Giraldo, J.D.[Juan D.], Alvarez-Meza, A.[Andres], Insuasti-Ceballos, D.[David], Bouwmans, T.[Thierry], Castellanos-Dominguez, G.[German],
GMM Background Modeling Using Divergence-Based Weight Updating,
CIARP16(282-290).
Springer DOI 1703
BibRef

Balcilar, M.[Muhammet], Sonmez, A.C.[A. Coskun],
Background estimation method with incremental iterative Re-weighted least squares,
SIViP(10), No. 1, January 2016, pp. 85-92.
WWW Link. 1601
BibRef

Li, L., Wang, P., Hu, Q., Cai, S.,
Efficient Background Modeling Based on Sparse Representation and Outlier Iterative Removal,
CirSysVideo(26), No. 2, February 2016, pp. 278-289.
IEEE DOI 1602
Bismuth BibRef

Yang, L.[Lu], Cheng, H.[Hong], Su, J.A.[Jian-An], Li, X.L.[Xue-Long],
Pixel-to-Model Distance for Robust Background Reconstruction,
CirSysVideo(26), No. 5, May 2016, pp. 903-916.
IEEE DOI 1605
Adaptation models BibRef

Liang, Y.L.[Yu-Ling], Shen, J.B.[Jian-Bing], Dong, X.P.[Xing-Ping], Sun, H.Q.[Han-Qiu], Li, X.L.[Xue-Long],
Video Supervoxels Using Partially Absorbing Random Walks,
CirSysVideo(26), No. 5, May 2016, pp. 928-938.
IEEE DOI 1605
Algorithm design and analysis BibRef

Qin, M., Lu, Y., Di, H., Huang, W.,
A Background Basis Selection-Based Foreground Detection Method,
MultMed(18), No. 7, July 2016, pp. 1283-1296.
IEEE DOI 1608
feature selection BibRef

Li, Z.H.[Zhi-Hui], Xia, Y.J.[Ying-Ji], Qu, Z.W.[Zhao-Wei],
Data-driven background representation method to video surveillance,
JOSA-A(34), No. 2, February 2017, pp. 193-202.
DOI Link 1702
Digital image processing BibRef

Elharrouss, O.[Omar], Abbad, A.[Abdelghafour], Moujahid, D.[Driss], Riffi, J.[Jamal], Tairi, H.[Hamid],
A block-based background model for moving object detection,
ELCVIA(15), No. 1, 2016, pp. 17-31.
DOI Link 1702
BibRef

Elharrouss, O.[Omar], Abbad, A.[Abdelghafour], Moujahid, D.[Driss], Tairi, H.[Hamid],
Moving object detection zone using a block-based background model,
IET-CV(12), No. 1, February 2018, pp. 86-94.
DOI Link 1801
BibRef

Elharrouss, O.[Omar], Moujahid, D.[Driss], Tairi, H.[Hamid],
Moving object detection with an adaptive background model,
ISCV17(1-5)
IEEE DOI 1710
Adaptation models, Analytical models, Computational modeling, Lighting, Measurement, Video sequences, Background model, Background subtraction, Motion detection, Video surveillance BibRef

Ramadan, H., Tairi, H.,
Pattern mining based video saliency detection,
ISCV17(1-6)
IEEE DOI 1710
Computational modeling, Feature extraction, Image color analysis, Prediction algorithms, Spatiotemporal phenomena, Visualization, image saliency, motion saliency, pattern mining algorithm, saliency patterns, spatiotemporal, saliency BibRef

Chen, G.[Gang], Zhang, H.Y.[Hai-Ying],
Category independent object discovery via background modeling,
PRL(87), No. 1, 2017, pp. 163-170.
Elsevier DOI 1703
Image segmentation BibRef

Lin, Y., Tong, Y., Cao, Y., Zhou, Y., Wang, S.,
Visual-Attention-Based Background Modeling for Detecting Infrequently Moving Objects,
CirSysVideo(27), No. 6, June 2017, pp. 1208-1221.
IEEE DOI 1706
Adaptation models, Cameras, Image color analysis, Object recognition, Optical imaging, Visualization, Yttrium, Infrequently moving objects, local motion stabilization, object detection, visual, attention BibRef

Wang, G.[Gang], Zhang, Y.D.[Yong-Dong], Li, J.T.[Jin-Tao],
High-level background prior based salient object detection,
JVCIR(48), No. 1, 2017, pp. 432-441.
Elsevier DOI 1708
Salient, object, detection BibRef

Lin, H.Y.[Hong-Yun], Lin, C.Y.[Chun-Yu], Zhao, Y.[Yao], Wang, A.H.[An-Hong],
3D saliency detection based on background detection,
JVCIR(48), No. 1, 2017, pp. 238-253.
Elsevier DOI 1708
3D saliency detection. BibRef

Bloisi, D.D.[Domenico D.], Pennisi, A.[Andrea], Iocchi, L.[Luca],
Background modeling in the maritime domain,
MVA(25), No. 5, July 2014, pp. 1257-1269.
WWW Link. 1407
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Bloisi, D.D.[Domenico D.], Pennisi, A.[Andrea], Iocchi, L.[Luca],
Parallel multi-modal background modeling,
PRL(96), No. 1, 2017, pp. 45-54.
Elsevier DOI 1709
Background, subtraction BibRef

Pennisi, A.[Andrea], Previtali, F., Bloisi, D.D.[Domenico D.], Iocchi, L.[Luca],
Real-time adaptive background modeling in fast changing conditions,
AVSS15(1-6)
IEEE DOI 1511
image sequences BibRef

Bouwmans, T.[Thierry], Maddalena, L.[Lucia], Petrosino, A.[Alfredo],
Scene background initialization: A taxonomy,
PRL(96), No. 1, 2017, pp. 3-11.
Elsevier DOI 1709
Background, initialization BibRef

Sobral, A.[Andrews], Zahzah, E.H.[El-Hadi],
Matrix and tensor completion algorithms for background model initialization: A comparative evaluation,
PRL(96), No. 1, 2017, pp. 22-33.
Elsevier DOI 1709
Matrix, completion BibRef

Ramirez-Alonso, G.[Graciela], Ramirez-Quintana, J.A.[Juan A.], Chacon-Murguia, M.I.[Mario I.],
Temporal weighted learning model for background estimation with an automatic re-initialization stage and adaptive parameters update,
PRL(96), No. 1, 2017, pp. 34-44.
Elsevier DOI 1709
Background, estimation BibRef

de Gregorio, M.[Massimo], Giordano, M.[Maurizio],
Background estimation by weightless neural networks,
PRL(96), No. 1, 2017, pp. 55-65.
Elsevier DOI 1709
Background, model BibRef

Avola, D.[Danilo], Cinque, L.[Luigi], Foresti, G.L.[Gian Luca], Massaroni, C.[Cristiano], Pannone, D.[Daniele],
A keypoint-based method for background modeling and foreground detection using a PTZ camera,
PRL(96), No. 1, 2017, pp. 96-105.
Elsevier DOI 1709
Background, modeling BibRef

Avola, D.[Danilo], Bernardi, M.[Marco], Cinque, L.[Luigi], Foresti, G.L.[Gian Luca], Massaroni, C.[Cristiano],
Adaptive bootstrapping management by keypoint clustering for background initialization,
PRL(100), No. 1, 2017, pp. 110-116.
Elsevier DOI 1712
Background initialization BibRef

Jodoin, P.M., Maddalena, L., Petrosino, A., Wang, Y.,
Extensive Benchmark and Survey of Modeling Methods for Scene Background Initialization,
IP(26), No. 11, November 2017, pp. 5244-5256.
IEEE DOI 1709
image resolution, video cameras, video signal processing, background image recovery, benchmarking framework, camera-captured videos, evaluation metrics, indoor scenes, outdoor scenes, scene background initialization methods, video data set, Benchmark testing, Image color analysis, Lighting, Measurement, Neural networks, Robustness, Sparse matrices, Background initialization, BibRef

Zhong, Z.F.[Zuo-Feng], Xu, Y.[Yong], Li, Z.Y.[Zuo-Yong], Zhao, Y.N.[Yin-Nan],
Background modelling using discriminative motion representation,
IET-CV(11), No. 6, September 2017, pp. 463-470.
DOI Link 1709
BibRef

Javed, S., Mahmood, A., Bouwmans, T., Jung, S.K.,
Background-Foreground Modeling Based on Spatiotemporal Sparse Subspace Clustering,
IP(26), No. 12, December 2017, pp. 5840-5854.
IEEE DOI 1710
principal component analysis, background estimation, motion-aware correlation coefficient, graph regularization, BibRef

Berjón, D.[Daniel], Cuevas, C.[Carlos], Morán, F.[Francisco], García, N.[Narciso],
Real-time nonparametric background subtraction with tracking-based foreground update,
PR(74), No. 1, 2018, pp. 156-170.
Elsevier DOI 1711
Foreground segmentation BibRef

Hua, K.L., Wang, H.C., Yeh, C.H., Cheng, W.H., Lai, Y.C.,
Background Extraction Using Random Walk Image Fusion,
Cyber(48), No. 1, January 2018, pp. 423-435.
IEEE DOI 1801
Algorithm design and analysis, Coherence, Computational modeling, Image color analysis, Image fusion, Videos, random walk (RW) BibRef

Zhang, C., Zhu, G., Liang, C., Zhang, Y., Huang, Q., Tian, Q.,
Image Class Prediction by Joint Object, Context, and Background Modeling,
CirSysVideo(28), No. 2, February 2018, pp. 428-438.
IEEE DOI 1802
Computational modeling, Context, Context modeling, Convolutional codes, Image representation, Image segmentation, object modeling BibRef

Kajo, I.[Ibrahim], Kamel, N.[Nidal], Ruichek, Y.[Yassine], Malik, A.S.[Aamir Saeed],
SVD-Based Tensor-Completion Technique for Background Initialization,
IP(27), No. 6, June 2018, pp. 3114-3126.
IEEE DOI 1804
Computational complexity, Feature extraction, Image reconstruction, Matrix converters, Matrix decomposition, tensor completion BibRef

Wu, X.Y.[Xi-Yin], Jin, Z.[Zhong], Zhou, J.B.[Jing-Bo], Ma, X.D.[Xiao-Di],
Saliency propagation with perceptual cues and background-excluded seeds,
JVCIR(54), 2018, pp. 51-62.
Elsevier DOI 1806
Saliency detection, Perceptual cue, Graph-based framework, Label propagation, Seed, Background probability BibRef

Ebadi, S.E.[Salehe Erfanian], Izquierdo, E.[Ebroul],
Foreground Segmentation with Tree-Structured Sparse RPCA,
PAMI(40), No. 9, September 2018, pp. 2273-2280.
IEEE DOI 1808
BibRef
Earlier:
Foreground Segmentation via Dynamic Tree-Structured Sparse RPCA,
ECCV16(I: 314-329).
Springer DOI 1611
Computational modeling, Sparse matrices, Robustness, Matrix decomposition, Cameras, Adaptation models, cohesive foreground segmentation BibRef

Ebadi, S.E., Ones, V.G., Izquierdo, E.,
Dynamic tree-structured sparse RPCA via column subset selection for background modeling and foreground detection,
ICIP16(3972-3976)
IEEE DOI 1610
Analytical models BibRef

Li, C.[Cong], Gao, L.[Lianru], Wu, Y.F.[Yuan-Feng], Zhang, B.[Bing], Plaza, J.[Javier], Plaza, A.[Antonio],
A real-time unsupervised background extraction-based target detection method for hyperspectral imagery,
RealTimeIP(14), No. 3, October 2018, pp. 597-615.
Springer DOI 1811
BibRef

Wu, Y.F.[Yuan-Feng], López, S.[Sebastián], Zhang, B.[Bing], Qiao, F.[Fei], Gao, L.R.[Lian-Ru],
Approximate computing for onboard anomaly detection from hyperspectral images,
RealTimeIP(16), No. 1, February 2019, pp. 99-114.
Springer DOI
WWW Link. 1902
BibRef

Wang, H., Lai, Y., Cheng, W., Cheng, C., Hua, K.,
Background Extraction Based on Joint Gaussian Conditional Random Fields,
CirSysVideo(28), No. 11, November 2018, pp. 3127-3140.
IEEE DOI 1811
Video sequences, Coherence, Lighting, Image reconstruction, Computational modeling, Data mining, Robustness, image fusion BibRef

Xu, Z.[Zhe], Min, B.[Biao], Cheung, R.C.C.[Ray C.C.],
A robust background initialization algorithm with superpixel motion detection,
SP:IC(71), 2019, pp. 1-12.
Elsevier DOI 1901
Background initialization, Superpixel, Motion detection, Density-based clustering BibRef

Djerida, A.[Achraf], Zhao, Z.H.[Zhong-Hua], Zhao, J.K.[Jian-Kang],
Robust background generation based on an effective frames selection method and an efficient background estimation procedure (FSBE),
SP:IC(78), 2019, pp. 21-31.
Elsevier DOI 1909
background generation, Background initialization, Video surveillance, Foreground detection BibRef

Erichson, N.B.[N. Benjamin], Brunton, S.L.[Steven L.], Kutz, J.N.[J. Nathan],
Compressed dynamic mode decomposition for background modeling,
RealTimeIP(16), No. 5, October 2019, pp. 1479-1492.
Springer DOI 1911
BibRef

Pendergrass, S., Brunton, S.L., Kutz, J.N., Erichson, N.B., Askham, T.,
Dynamic Mode Decomposition for Background Modeling,
RSL-CV17(1862-1870)
IEEE DOI 1802
Approximation algorithms, Computational modeling, Eigenvalues and eigenfunctions, Heuristic algorithms, Technological innovation BibRef

Kajo, I., Kamel, N., Ruichek, Y.[Yassine],
Self-Motion-Assisted Tensor Completion Method for Background Initialization in Complex Video Sequences,
IP(29), No. 1, 2020, pp. 1915-1928.
IEEE DOI 1912
Lighting, Spatiotemporal phenomena, Video sequences, Feature extraction, Clutter, Data mining, clutter BibRef

Chen, A.T.Y.[Andrew Tzer-Yeu], Biglari-Abhari, M.[Morteza], Wang, K.I.K.[Kevin I-Kai],
SuperBE: computationally light background estimation with superpixels,
RealTimeIP(16), No. 6, December 2019, pp. 2319-2335.
Springer DOI 1912
BibRef

Zhang, J., Jia, X., Hu, J.,
Error Bounded Foreground and Background Modeling for Moving Object Detection in Satellite Videos,
GeoRS(58), No. 4, April 2020, pp. 2659-2669.
IEEE DOI 2004
Videos, Satellites, Matrix decomposition, Object detection, Spatial resolution, Data models, Optimization, structured sparsity-inducing norm BibRef

Zhang, J., Jia, X., Hu, J., Chanussot, J.,
Online Structured Sparsity-Based Moving-Object Detection From Satellite Videos,
GeoRS(58), No. 9, September 2020, pp. 6420-6433.
IEEE DOI 2008
Matrix decomposition, Videos, Optimization, Satellites, Sparse matrices, Convergence, Delays, Background subtraction, structured sparsity-inducing norm BibRef

Tocker, Y., Hagege, R.R., Francos, J.M.,
Dynamic Spatial Predicted Background,
IP(29), 2020, pp. 5517-5530.
IEEE DOI 2005
Background modeling, foreground-background separation, motion detection, spatial prediction, video analysis BibRef

Matczak, G.[Grzegorz], Mazurek, P.[Przemyslaw],
Comparative Monte Carlo Analysis of Background Estimation Algorithms for Unmanned Aerial Vehicle Detection,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Huang, C.R.[Chun-Rong], Huang, W.Y.[Wei-Yun], Liao, Y.S.[Yi-Sheng], Lee, C.C.[Chien-Cheng], Yeh, Y.W.[Yu-Wei],
A Content-Adaptive Resizing Framework for Boosting Computation Speed of Background Modeling Methods,
SMCS(52), No. 2, February 2022, pp. 1192-1204.
IEEE DOI 2201
Graphics processing units, Videos, Acceleration, High definition video, Surveillance, superpixels BibRef

Rong, J.X.[Jian-Xiang], Zhang, L.[Lei], Huang, H.[Hua], Zhang, F.L.[Fang-Lue],
IMU-Assisted Online Video Background Identification,
IP(31), 2022, pp. 4336-4351.
IEEE DOI 2207
Cameras, Trajectory, Motion segmentation, Object recognition, Streaming media, Background identification, online, offset BibRef

He, W.[Wei], Li, J.X.[Jie-Xin], Qi, Q.[Qi], Tu, B.[Bing], Ou, X.F.[Xian-Feng], Guo, L.Y.[Long-Yuan],
SIM-MFR: Spatial interactions mechanisms based multi-feature representation for background modeling,
JVCIR(88), 2022, pp. 103622.
Elsevier DOI 2210
Object detection, Dynamic backgrounds, K-means, Multi-feature, Complementary notion BibRef

Han, J.[Juan], Kou, K.I.[Kit Ian], Miao, J.[Jifei],
Quaternion-based dynamic mode decomposition for background modeling in color videos,
CVIU(224), 2022, pp. 103560.
Elsevier DOI 2211
Background model initialization, Color videos, Dynamic mode decomposition, Quaternion BibRef

Zhou, W.J.[Wen-Jun], Deng, Y.H.[Yu-Heng], Peng, B.[Bo], Xiang, S.[Sheng], Kaneko, S.[Shun'ichi],
Co-occurrence spatial-temporal model for adaptive background initialization in high-dynamic complex scenes,
SP:IC(119), 2023, pp. 117056.
Elsevier DOI 2310
Background initialization, Spatial-Temporal model, Foreground detection, High-dynamic complex scene BibRef

Fang, Z.[Zheng], Zheng, M.K.[Ming-Kui], Chen, P.P.[Ping-Ping], Chen, Z.F.[Zhi-Feng], Wu, D.P.O.[Da-Peng Oliver],
Camera Pose-Based Background Modeling for Video Coding in Moving Cameras,
CirSysVideo(34), No. 5, May 2024, pp. 4054-4069.
IEEE DOI 2405
Cameras, Encoding, Video coding, Bit rate, Predictive models, Estimation, Computational modeling, Video coding, camera pose, moving cameras BibRef

Eshratifar, A.E.[Amir Erfan], Soares, J.V.B.[João V. B.], Thadani, K.[Kapil], Mishra, S.[Shaunak], Kuznetsov, M.[Mikhail], Ku, Y.N.[Yueh-Ning], de Juan, P.[Paloma],
Salient Object-Aware Background Generation using Text-Guided Diffusion Models,
GCV24(7489-7499)
IEEE DOI 2410
Measurement, Degradation, Adaptation models, Visualization, Diffusion models, background-generation BibRef

Park, G.[Gilhan], Moon, W.[WonJun], Lee, S.[SuBeen], Kim, T.Y.[Tae-Young], Heo, J.P.[Jae-Pil],
Mitigating Background Shift in Class-incremental Semantic Segmentation,
ECCV24(L: 71-88).
Springer DOI 2412
BibRef

Erez, G.[Guy], Weber, R.S.[Ron Shapira], Freifeld, O.[Oren],
A Deep Moving-Camera Background Model,
ECCV22(XXXV:177-194).
Springer DOI 2211
BibRef

Chen, J.W.[Jun-Wen], Mittal, G.[Gaurav], Yu, Y.[Ye], Kong, Y.[Yu], Chen, M.[Mei],
GateHUB: Gated History Unit with Background Suppression for Online Action Detection,
CVPR22(19893-19902)
IEEE DOI 2210
Image motion analysis, Logic gates, Streaming media, Predictive models, Transformers, Action and event recognition BibRef

Mullapudi, R.T.[Ravi Teja], Poms, F.[Fait], Mark, W.R.[William R.], Ramanan, D.[Deva], Fatahalian, K.[Kayvon],
Background Splitting: Finding Rare Classes in a Sea of Background,
CVPR21(8039-8048)
IEEE DOI 2111
Training, Computational modeling, Predictive models, Data models, Task analysis BibRef

Wang, J.P.[Jin-Peng], Gao, Y.T.[Yu-Ting], Li, K.[Ke], Lin, Y.Q.[Yi-Qi], Ma, A.J.[Andy J.], Cheng, H.[Hao], Peng, P.[Pai], Huang, F.Y.[Fei-Yue], Ji, R.R.[Rong-Rong], Sun, X.[Xing],
Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning,
CVPR21(11799-11808)
IEEE DOI 2111
Deep learning, Force, Focusing, Resists, Predictive models, Benchmark testing BibRef

Cruz, R.[Ricardo], Prates, R.M.[Ricardo M.], Filho, E.F.S.[Eduardo F. Simas], Costa, J.F.P.[Joaquim F. Pinto], Cardoso, J.S.[Jaime S.],
Background Invariance by Adversarial Learning,
ICPR21(5883-5888)
IEEE DOI 2105
Training, Image segmentation, Satellites, Semantics, Reinforcement learning, Insulators, Robustness BibRef

Liu, S., Lehman, C., Al Regib, G.,
Robustness and Overfitting Behavior of Implicit Background Models,
ICIP20(3274-3278)
IEEE DOI 2011
Testing, Training, Data models, Image segmentation, Transforms, Calibration, Numerical models, Image classification, data augmentation BibRef

Rezaei, B.[Behnaz], Farnoosh, A.[Amirreza], Ostadabbas, S.[Sarah],
DEEPPBM: Deep Probabilistic Background Model Estimation from Video Sequences,
DLPR20(608-621).
Springer DOI 2103
BibRef
Earlier:
G-LBM: Generative Low-dimensional Background Model Estimation from Video Sequences,
ECCV20(XII: 293-310).
Springer DOI 2010
BibRef

Lehman, C., Temel, D., AlRegib, G.,
Implicit Background Estimation For Semantic Segmentation,
ICIP19(1935-1939)
IEEE DOI 1910
Scene understanding, semantic segmentation, robustness, out-of-distribution detection, model calibration BibRef

Avola, D.[Danilo], Bernardi, M.[Marco], Cascio, M.[Marco], Cinque, L.[Luigi], Foresti, G.L.[Gian Luca], Massaroni, C.[Cristiano],
A New Descriptor for Keypoint-Based Background Modeling,
CIAP19(I:15-25).
Springer DOI 1909
BibRef

Lin, K.[Kaimo], Jiang, N.[Nianjuan], Cheong, L.F.[Loong Fah], Lu, J.B.[Jiang-Bo], Xu, X.[Xun],
Robust Video Background Identification by Dominant Rigid Motion Estimation,
ACCV18(II:163-178).
Springer DOI 1906
BibRef

Patil, P., Murala, S.,
FgGAN: A Cascaded Unpaired Learning for Background Estimation and Foreground Segmentation,
WACV19(1770-1778)
IEEE DOI 1904
image motion analysis, image segmentation, image sequences, learning (artificial intelligence), Histograms BibRef

Xie, H.G.[Hong Gang], Xiao, J.S.[Jin Sheng], Lei, J.F.[Jun Feng],
Context-Awareness Based Adaptive Gaussian Mixture Background Modeling,
PSIVTWS17(415-425).
Springer DOI 1806
BibRef

Kim, J., Rivera, A.R., Kim, B., Roy, K., Chae, O.,
Background modeling using adaptive properties of hybrid features,
AVSS17(1-6)
IEEE DOI 1806
adaptive signal processing, image colour analysis, image matching, image representation, ADM, Shape BibRef

Tao, Y., Palasek, P., Ling, Z., Patras, I.,
Background modelling based on generative unet,
AVSS17(1-6)
IEEE DOI 1806
image colour analysis, image motion analysis, image segmentation, image sequences, learning (artificial intelligence), Training BibRef

Varadarajan, S., Wang, H., Scotney, B., Nibouche, O.,
Background initialisation by spatio-temporal motion estimation,
AVSS17(1-5)
IEEE DOI 1806
image motion analysis, image sequences, motion estimation, object detection, video signal processing, SBI, Video sequences BibRef

Shallari, I., Anwar, Q., Imran, M., O'Nils, M.,
Background modelling, analysis and implementation for thermographic images,
IPTA17(1-6)
IEEE DOI 1804
Gaussian processes, IIR filters, image processing, infrared imaging, nearest neighbour methods, pipelines, visual BibRef

Siva, P., Jamieson, M.,
Scale-Corrected Background Modeling,
CRV17(292-298)
IEEE DOI 1804
calibration, cameras, image resolution, image sensors, object detection, video signal processing, video surveillance, scale normalization BibRef

Takeishi, N.[Naoya], Kawahara, Y.[Yoshinobu], Yairi, T.[Takehisa],
Sparse nonnegative dynamic mode decomposition,
ICIP17(2682-2686)
IEEE DOI 1803
Aerodynamics, Eigenvalues and eigenfunctions, Heuristic algorithms, Optimization, Power system dynamics, sparse modeling BibRef

Zhang, Z.[Zhe], Wong, K.H.[Kin Hong], Zeng, Z.L.[Zhi-Liang], Zhu, L.[Lei],
A neural network approach to visual tracking,
MVA17(382-385)
DOI Link 1708
Benchmark testing, Image segmentation, Mathematical model, Neural networks, Target tracking, Training, Visualization BibRef

Liu, W.[Wei], Cai, Y.Z.[Yuan-Zheng], Zhang, M.H.[Miao-Hui], Li, H.[Hui], Gu, H.J.[He-Jin],
Scene background estimation based on temporal median filter with Gaussian filtering,
ICPR16(132-136)
IEEE DOI 1705
Clutter, Colored noise, Computational modeling, Estimation, Image color analysis, Robustness, Video, sequences BibRef

Halfaoui, I., Bouzaraa, F., Urfalioglu, O.,
CNN-based initial background estimation,
ICPR16(101-106)
IEEE DOI 1705
Adaptation models, Cameras, Estimation, Lighting, Reliability, Training BibRef

Yi, R., Wang, J., Tan, P.,
Automatic Fence Segmentation in Videos of Dynamic Scenes,
CVPR16(705-713)
IEEE DOI 1612
BibRef

Tirunagari, S., Poh, N., Bober, M., Windridge, D.,
Can DMD obtain a Scene Background in color?,
ICIVC16(46-50)
IEEE DOI 1610
Dynamic Mode Decomposition. Video into foreground/background. image colour analysis BibRef

Elharrouss, O., Moujahid, D., Elkaitouni, S.E., Tairi, H.,
An Effective Foreground Detection Approach Using a Block-Based Background Modeling,
CGiV16(190-195)
IEEE DOI 1608
image segmentation BibRef

Theiler, J.,
Generic target response as a measure of regression accuracy in multispectral background estimation,
Southwest16(45-48)
IEEE DOI 1605
Covariance matrices BibRef

Wang, C., Yang, B.,
Saliency-guided object proposal for refined salient region detection,
VCIP16(1-4)
IEEE DOI 1701
BibRef
Earlier:
An unsupervised object-level image segmentation method based on foreground and background priors,
Southwest16(141-144)
IEEE DOI 1605
Image color analysis BibRef

Li, J.L.[Jun-Ling], Meng, F.[Fang], Zhang, Y.C.[Yi-Chun],
Saliency detection using a background probability model,
ICIP15(2189-2193)
IEEE DOI 1512
background priors BibRef

Rodger, I.[Iain], Connor, B.[Barry], Robertson, N.M.[Neil M.],
Recovering background regions in videos of cluttered urban scenes,
ICIP15(4097-4101)
IEEE DOI 1512
Foreground Context, Image Segmentation, Superpixels BibRef

Noceti, N.[Nicoletta], Staglianò, A.[Alessandra], Verri, A.[Alessandro], Odone, F.[Francesca],
BMTDL for Scene Modeling on the SBI Dataset,
SBMI15(502-509).
Springer DOI 1511
Background Modeling Through Dictionary Learning. Scene Background Initialization. BibRef

Bloisi, D.D.[Domenico D.], Grillo, A.[Alfonso], Pennisi, A.[Andrea], Iocchi, L.[Luca], Passaretti, C.[Claudio],
Multi-modal Background Model Initialization,
SBMI15(485-492).
Springer DOI 1511
BibRef

Maddalena, L.[Lucia], Petrosino, A.[Alfredo],
Extracting a background image by a multi-modal scene background model,
ICPR16(143-148)
IEEE DOI 1705
Adaptation models, Analytical models, Biological neural networks, Computational modeling, Estimation, Image sequences, Training BibRef

Maddalena, L.[Lucia], Petrosino, A.[Alfredo],
Towards Benchmarking Scene Background Initialization,
SBMI15(469-476).
Springer DOI 1511
Dataset:
See also Scene Background Initialization (SBI) Dataset. BibRef

Sobral, A.[Andrews], Bouwmans, T.[Thierry], Zahzah, E.H.[El-Hadi],
Comparison of Matrix Completion Algorithms for Background Initialization in Videos,
SBMI15(510-518).
Springer DOI 1511
BibRef

Renó, V.[Vito], Marani, R.[Roberto], Mosca, N.[Nicola], Nitti, M.[Massimiliano], d'Orazio, T.[Tiziana], Stella, E.[Ettore],
A Likelihood-Based Background Model for Real Time Processing of Color Filter Array Videos,
ISCA15(218-225).
Springer DOI 1511
BibRef

Zhao, J.[Jing], Pang, S.N.[Shao-Ning], Hartill, B.[Bruce], Sarrafzadeh, A.[AbdolHossein],
Adaptive Background Modeling for Land and Water Composition Scenes,
CIAP15(II:97-107).
Springer DOI 1511
BibRef

Maeda, T.[Tomosuke], Ohtsuka, T.[Tomohiko],
Reliable background prediction using approximated GMM,
MVA15(142-145)
IEEE DOI 1507
Computational modeling BibRef

Itoh, M.,
Robust object detection and adaptive background estimation based on radial reach correlation,
FCV15(1-5)
IEEE DOI 1506
correlation methods BibRef

Rodriguez, P.[Paul], Wohlberg, B.[Brendt],
Translational and rotational jitter invariant incremental principal component pursuit for video background modeling,
ICIP15(537-541)
IEEE DOI 1512
BibRef
Earlier:
A Matlab implementation of a fast incremental principal component pursuit algorithm for Video Background Modeling,
ICIP14(3414-3416)
IEEE DOI 1502
Principal Component Pursuit. Cameras BibRef

Rodriguez, P.[Paul], Wohlberg, B.[Brendt],
Incremental Principal Component Pursuit for Video Background Modeling,
JMIV(55), No. 1, May 2016, pp. 1-18.
WWW Link. 1604
BibRef

Rodriguez, P.[Paul], Chau, G.,
Panning and Jitter Invariant Incremental Principal Component Pursuit for Video Background Modeling,
RSL-CV17(1844-1852)
IEEE DOI 1802
Cameras, Computational modeling, Estimation, Jitter, Optimization, Robustness, Sparse matrices BibRef

Tiefenbacher, P.[Philipp], Hofmann, M.[Martin], Merget, D.[Daniel], Rigoll, G.[Gerhard],
PID-based regulation of background dynamics for foreground segmentation,
ICIP14(3282-3286)
IEEE DOI 1502
Adaptation models BibRef

Zhang, Y.B.[Yan-Bang], Han, J.W.[Jun-Wei], Guo, L.[Lei],
Salient region detection using background contrast,
ICIP14(1184-1188)
IEEE DOI 1502
Computational modeling BibRef

Li, Y.J.[Yi-Jun], Fu, K.[Keren], Zhou, L.[Lei], Qiao, Y.[Yu], Yang, J.[Jie],
Saliency detection via foreground rendering and background exclusion,
ICIP14(3263-3267)
IEEE DOI 1502
Benchmark testing BibRef

Lu, X.[Xiqun],
A multiscale spatio-temporal background model for motion detection,
ICIP14(3268-3271)
IEEE DOI 1502
Color BibRef

Rodriguez, P.[Paul], Wohlberg, B.[Brendt],
Video background modeling under impulse noise,
ICIP14(1041-1045)
IEEE DOI 1502
Approximation algorithms BibRef

Giordano, D.[Daniela], Palazzo, S.[Simone], Spampinato, C.[Concetto],
Kernel Density Estimation Using Joint Spatial-Color-Depth Data for Background Modeling,
ICPR14(4388-4393)
IEEE DOI 1412
Cameras BibRef

Lin, C.W.[Chih-Wei], Liao, W.J.[Wei-Jie], Chen, C.S.[Chu-Song], Hung, Y.P.[Yi-Ping],
A spatiotemporal background extractor using a single-layer codebook model,
AVSS14(259-264)
IEEE DOI 1411
Brightness BibRef

Sedky, M.[Mohamed], Moniri, M.[Mansour], Chibelushi, C.C.[Claude C.],
Spectral-360: A Physics-Based Technique for Change Detection,
CDW14(405-408)
IEEE DOI 1409
background modelling BibRef

Mumtaz, A.[Adeel], Zhang, W.C.[Wei-Chen], Chan, A.B.[Antoni B.],
Joint Motion Segmentation and Background Estimation in Dynamic Scenes,
CVPR14(368-375)
IEEE DOI 1409
Background estimation, Dynamic texture, Motion segmentation BibRef

Wei, C.P.[Chia-Po], Huang, Y.M.[Yen-Ming], Wang, Y.C.F., Shih, M.Y.[Ming-Yu],
Background Recovery in Railroad Crossing Videos via Incremental Low-Rank Matrix Decomposition,
ACPR13(702-706)
IEEE DOI 1408
image recognition BibRef

Liu, W.C.[Wan-Chen], Lin, S.Z.[Shu-Zhe], Yang, M.H.[Min-Hsiang], Huang, C.R.[Chun-Rong],
Real-Time Binary Descriptor Based Background Modeling,
ACPR13(722-726)
IEEE DOI 1408
feature extraction BibRef

Zhao, W., Zhao, X.D., Liu, W.M., Tang, X.L.,
Long-term background memory based on Gaussian mixture model,
VCIP13(1-5)
IEEE DOI 1402
Gaussian processes BibRef

Lai, J.[Jian], Leow, W.K.[Wee Kheng], Sim, T.[Terence],
Incremental Fixed-Rank Robust PCA for Video Background Recovery,
CAIP15(II:652-663).
Springer DOI 1511
BibRef

Leow, W.K.[Wee Kheng], Cheng, Y.[Yuan], Zhang, L.[Li],
Background Recovery by Fixed-Rank Robust Principal Component Analysis,
CIAP13(54-61).
Springer DOI 1308
BibRef

Glazer, A.[Assaf], Lindenbaum, M.[Michael], Markovitch, S.[Shaul],
One-Class Background Model,
BMC12(I:301-307).
Springer DOI 1304
BibRef

Shah, M.[Munir], Deng, J.D.[Jeremiah D.], Woodford, B.J.[Brendon J.],
A Self-adaptive CodeBook (SACB) model for real-time background subtraction,
IVC(38), No. 1, 2015, pp. 52-64.
Elsevier DOI 1506
BibRef
Earlier:
Improving Mixture of Gaussians background model through adaptive learning and Spatio-Temporal voting,
ICIP13(3436-3440)
IEEE DOI 1402
BibRef
Earlier:
Illumination Invariant Background Model Using Mixture of Gaussians and SURF Features,
BMC12(I:308-314).
Springer DOI 1304
BibRef
Earlier:
Localized adaptive learning of Mixture of Gaussians models for background extraction,
IVCNZ10(1-8).
IEEE DOI 1203
Mixture of Gaussians, foreground detection, video processing. Background subtraction.
See also Video background modeling: Recent Approaches, Issues and Our Proposed Techniques. BibRef

Hughes, K.[Kevin], Grzeda, V.[Victor], Greenspan, M.[Michael],
Eigenbackground Bootstrapping,
CRV13(196-201)
IEEE DOI 1308
Adaptation models BibRef

Zhang, R.[Rui], Gong, W.G.[Wei-Guo], Yaworski, A.[Andrew], Greenspan, M.[Michael],
Nonparametric on-line background generation for surveillance video,
ICPR12(1177-1180).
WWW Link. 1302
BibRef

Alahi, A.[Alexandre], Bagnato, L.[Luigi], Matti, D.[Damien], Vandergheynst, P.[Pierre],
Foreground silhouette extraction robust to sudden changes of background appearance,
ICIP12(1229-1232).
IEEE DOI 1302
BibRef

Yatagawa, T.[Tatsuya], Yamaguchi, Y.S.[Yasu-Shi],
A Template-based Completion Framework for Videos with Dynamic Backgrounds,
ISVC12(II: 155-165).
Springer DOI 1209
BibRef

Salvadori, C.[Claudio], Makris, D.[Dimitrios], Petracca, M.[Matteo], Martinez-del-Rincon, J.[Jesus], Velastin, S.A.[Sergio A.],
Gaussian Mixture Background Modelling Optimisation for Micro-controllers,
ISVC12(I: 241-251).
Springer DOI 1209
for parallel implementations. BibRef

Martel-Brisson, N.[Nicolas], Zaccarin, A.[André],
Unsupervised approach for building non-parametric background and foreground models of scenes with significant foreground activity,
VNBA08(93-100).
DOI Link 1208
Background statistics at the cannot be described parametrically. BibRef

Aghazadeh, O.[Omid], Sullivan, J.[Josephine], Carlsson, S.[Stefan],
Multi view registration for novelty/background separation,
CVPR12(757-764).
IEEE DOI 1208
BibRef

Borji, A.[Ali], Frintrop, S.[Simone], Sihite, D.N.[Dicky N.], Itti, L.[Laurent],
Adaptive object tracking by learning background context,
Egocentric12(23-30).
IEEE DOI 1207
BibRef

Morde, A.[Ashutosh], Ma, X.[Xiang], Guler, S.[Sadiye],
Learning a background model for change detection,
CDW12(15-20).
IEEE DOI 1207
BibRef

Hofmann, M.[Martin], Tiefenbacher, P.[Philipp], Rigoll, G.[Gerhard],
Background segmentation with feedback: The Pixel-Based Adaptive Segmenter,
CDW12(38-43).
IEEE DOI 1207
BibRef

Schick, A.[Alexander], Bauml, M.[Martin], Stiefelhagen, R.[Rainer],
Improving foreground segmentations with probabilistic superpixel Markov random fields,
CDW12(27-31).
IEEE DOI 1207
BibRef

Benalia, M.[Mohcene], Ait-Aoudia, S.[Samy],
An Improved Basic Sequential Clustering Algorithm for Background Construction and Motion Detection,
ICIAR12(I: 216-223).
Springer DOI 1206
BibRef

Yuk, J.S.C., Wong, K.Y.K.,
An efficient pattern-less background modeling based on scale invariant local states,
AVSBS11(285-290).
IEEE DOI 1111
BibRef

Kirchhof, M.[Michael], Stilla, U.[Uwe],
Statistical Unbiased Background Modeling for Moving Platforms,
PIA11(245-256).
Springer DOI 1110
BibRef

Li, D.W.[Da-Wei], Xu, L.H.[Li-Hong], Goodman, E.,
Online background learning for illumination-robust foreground detection,
ICARCV10(1093-1100).
IEEE DOI 1109
BibRef

Li, P.[Peng], Wang, C.H.[Chen-Hao], Wang, C.J.[Chong-Jing], Liu, Y.C.[Yun-Cai],
Adaptive Background Model for Arbitrary-Long Stationary Target,
ICIG11(558-561).
IEEE DOI 1109
BibRef

Quivy, C.H.[Charles-Henri], Kumazawa, I.[Itsuo],
Background Images Generation Based on the Nelder-Mead Simplex Algorithm Using the Eigenbackground Model,
ICIAR11(I: 21-29).
Springer DOI 1106
BibRef

Su, T.F.[Te-Feng], Chen, Y.L.[Yi-Ling], Lai, S.H.[Shang-Hong],
Over-Segmentation Based Background Modeling and Foreground Detection with Shadow Removal by Using Hierarchical MRFs,
ACCV10(III: 535-546).
Springer DOI 1011
BibRef

Jarraya, S.K.[Salma Kammoun], Hammami, M.[Mohamed], Ben-Abdallah, H.[Hanene],
Accurate Background Modeling for Moving Object Detection in a Dynamic Scene,
DICTA10(52-57).
IEEE DOI 1012
BibRef

Paul, M.[Manoranjan], Lin, W.S.[Wei-Si], Lau, C.T.[Chiew Tong], Lee, B.S.[Bu-Sung],
Pattern based video coding with uncovered background,
ICIP10(2065-2068).
IEEE DOI 1009
BibRef

Yam, K.Y.[Kin-Yi], Siu, W.C.[Wan-Chi], Law, N.F.[Ngai-Fong], Chan, C.K.[Chok-Ki],
Fast video object detection via multiple background modeling,
ICIP10(729-732).
IEEE DOI 1009
BibRef

Huang, T.[Tianci], Qiu, J.B.[Jing-Bang], Sakayori, T.[Takahiro], Ikenaga, T.[Takeshi],
Robust Background Segmentation Using Background Models for Surveillance Application,
MVA09(402-).
PDF File. 0905
BibRef

Baltieri, D., Vezzani, R., Cucchiara, R.,
Fast Background Initialization with Recursive Hadamard Transform,
AVSS10(165-171).
IEEE DOI 1009
BibRef

Scott, J., Pusateri, M.A., Cornish, D.,
Kalman filter based video background estimation,
AIPR09(1-7).
IEEE DOI 0910
BibRef

Kita, Y.[Yasuyo],
Background Modeling by Combining Joint Intensity Histogram with Time-sequential Data,
ICPR10(991-994).
IEEE DOI 1008
BibRef

Forczmanski, P.[Pawel], Seweryn, M.[Marcin],
Surveillance Video Stream Analysis Using Adaptive Background Model and Object Recognition,
ICCVG10(I: 114-121).
Springer DOI 1009
BibRef

Uegaki, H.[Hiroshi], Nakashima, Y.[Yuta], Babaguchi, N.[Noboru],
Discriminating Intended Human Objects in Consumer Videos,
ICPR10(4380-4383).
IEEE DOI 1008
BibRef

Nakashima, Y.[Yuta], Babaguchi, N.[Noboru], Fan, J.P.[Jian-Ping],
Detecting intended human objects in human-captured videos,
POCV10(33-40).
IEEE DOI 1006
I.e. what the person intended to capture in the video. BibRef

Liu, X.D.[Xue-Dong], Wang, H.[Hong],
A fast motion segmentation algorithm based on hypothesis test for surveillance video coding,
IASP10(653-655).
IEEE DOI 1004
BibRef

Kawanishi, Y.[Yasutomo], Funatomi, T.[Takuya], Kakusho, K.[Koh], Minoh, M.[Michihiko],
Background Estimation Based on Device Pixel Structures for Silhouette Extraction,
ACCV09(III: 140-151).
Springer DOI 0909
BibRef

Vemulapalli, R.[Raviteja], Aravind, R.,
Spatio-temporal nonparametric background modeling and subtraction,
VS09(1145-1152).
IEEE DOI 0910
BibRef

Sznitman, R.[Raphael], Lin, H.[Henry], Gupta, M.[Manaswi], Hager, G.[Gregory],
Active background modeling: Actors on a stage,
VS09(1222-1228).
IEEE DOI 0910
BibRef

Maludrottu, S., Regazzoni, C.S., Sallam, H., Talkhan, I., Atiya, A.,
Corner-based background segmentation using Adaptive Resonance Theory,
ICIP09(3201-3204).
IEEE DOI 0911
BibRef

Zhong, B.[Bineng], Yao, H.X.[Hong-Xun], Liu, S.H.[Shao-Hui],
Neighboring Image Patches Embedding for background modeling,
ICIP09(3209-3212).
IEEE DOI 0911
BibRef

Kim, H.S.[Han-Sung], Hilton, A.[Adrian],
Graph-based foreground extraction in extended color space,
ICIP09(3221-3224).
IEEE DOI 0911
BibRef

Suau, X.[Xavier], Casas, J.R.[Josep R.], Ruiz-Hidalgo, J.[Javier],
Multi-Resolution Illumination Compensation for foreground extraction,
ICIP09(3225-3228).
IEEE DOI 0911
BibRef

Li, H.[Hao], Achim, A.[Alin], Bull, D.R.[David R.],
GMM-based efficient foreground detection with adaptive region update,
ICIP09(3181-3184).
IEEE DOI 0911
BibRef

Reddy, V.[Vikas], Sanderson, C.[Conrad], Lovell, B.C.[Brian C.],
An efficient and robust sequential algorithm for background estimation in video surveillance,
ICIP09(1109-1112).
IEEE DOI 0911
BibRef

Almeida, M.S.C.[Mariana S. C.], Almeida, L.B.[Luis B.],
Blind deblurring of foreground-background images,
ICIP09(1301-1304).
IEEE DOI 0911
BibRef

Choudri, S.[Saad], Ferryman, J.M.[James M.], Badii, A.[Atta],
Robust background model for pixel based people counting using a single uncalibrated camera,
PETS-Winter09(1-8).
IEEE DOI 0912
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Sweet, J.N.[James N.],
Dominant component suppression with applications to spectral analysis,
AIPR08(1-7).
IEEE DOI 0810
Background supression. BibRef

Haque, M.[Mahfuzul], Murshed, M.[Manzur], Paul, M.[Manoranjan],
Improved Gaussian mixtures for robust object detection by adaptive multi-background generation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Sinha, A.K.[Akhilesh K.], Guha, P.[Prithwijit], Mukerjee, A.[Amitabha],
Back to the future: Robust foreground extraction with reversed-time background modeling,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Rosell-Ortega, J., Andreu-Garcia, G., Rodas-Jorda, A., Atienza-Vanacloig, V.,
Background modelling in demanding situations with confidence measure,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Zhao, Y.J.[Yi-Jia], Casares, M.[Mauricio], Velipasalar, S.[Senem],
Continuous Background Update and Object Detection with Non-static Cameras,
AVSBS08(309-316).
IEEE DOI 0809
BibRef

Chen, C.C.[Chia-Chih], Aggarwal, J.K.,
An adaptive background model initialization algorithm with objects moving at different depths,
ICIP08(2664-2667).
IEEE DOI 0810
BibRef

Krishna, R.[Radha], McCusker, K.[Kealan], O'Connor, N.E.[Noel E.],
Optimising resource allocation for background modeling using algorithm switching,
ICDSC08(1-7).
IEEE DOI 0809
BibRef

Liu, Y.X.[Yan-Xi], Belkina, T.[Tamara], Hays, J.H.[James H.], Lublinerman, R.[Roberto],
Image de-fencing,
CVPR08(1-8).
IEEE DOI 0806
Translational symmetry for foreground/background separation. BibRef

Xu, X.[Xun], Huang, T.S.[Thomas S.],
A Loopy Belief Propagation approach for robust background estimation,
CVPR08(1-7).
IEEE DOI 0806
BibRef

Hu, W.Z.[Wen-Ze], Wen, J.T.[Jian-Ting], Gong, H.F.[Hai-Feng], Wang, Y.T.[Yong-Tian],
An interactive scene annotation tool for video surveillance,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Hu, W.Z.[Wen-Ze], Gong, H.F.[Hai-Feng], Zhu, S.C.[Song-Chun], Wang, Y.T.[Yong-Tian],
An integrated background model for video surveillance based on primal sketch and 3D scene geometry,
CVPR08(1-8).
IEEE DOI 0806

See also Intrackability: Characterizing Video Statistics and Pursuing Video Representations. BibRef

Monari, E.[Eduardo], Pasqual, C.[Charlotte],
Fusion of background estimation approaches for motion detection in non-static backgrounds,
AVSBS07(347-352).
IEEE DOI 0709
BibRef

Han, B.H.[Bo-Hyung], Jain, R.[Ramesh],
Real-Time Subspace-Based Background Modeling Using Multi-channel Data,
ISVC07(II: 162-172).
Springer DOI 0711
BibRef

Nomura, N.[Naobumi], Kitahara, I.[Itaru], Kameda, Y.[Yoshinari], Ohta, Y.[Yuichi],
A Background Modeling Method with Simple Operations for 3D Video,
3DTV07(1-4).
IEEE DOI 0705
BibRef

Ye, G.[Getian],
High-Resolution Multi-sprite Generation for Background Sprite Coding,
ACIVS07(756-767).
Springer DOI 0708
BibRef

Ren, X.F.[Xiao-Feng], Malik, J.[Jitendra],
Tracking as Repeated Figure/Ground Segmentation,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Cheng, S.[Steven], Luo, X.Z.[Xing-Zhi], Bhandarkar, S.M.[Suchendra M.],
A Multiscale Parametric Background Model for Stationary Foreground Object Detection,
Motion07(18-18).
IEEE DOI 0702
BibRef

Luo, X.Z.[Xing-Zhi], Bhandarkar, S.M., Hua, W.[Wei], Gu, H.S.[Hai-Song],
Nonparametric Background Modeling Using the CONDENSATION Algorithm,
AVSBS06(3-3).
IEEE DOI 0611
BibRef

Park, D.Y.[Dae-Yong], Byun, H.R.[Hye-Ran],
Object-Wise Multilayer Background Ordering for Public Area Surveillance,
AVSBS09(484-489).
IEEE DOI 0909
BibRef

Jacobs, N., Pless, R.,
Shape Background Modeling: The Shape of Things That Came,
Motion07(27-27).
IEEE DOI 0702
Background modeling using expected shape of foreground objects. BibRef

Campbell-West, F., Miller, P., Wang, H.B.[Hong-Bin],
Independent Moving Object Detection Using a Colour Background Model,
AVSBS06(31-31).
IEEE DOI 0611
BibRef

Kim, T.K.[Tae-Kyung], Paik, J.K.[Joon-Ki],
Adaptive Background Generation for Video Object Segmentation,
ISVC06(I: 871-880).
Springer DOI 0611
BibRef

Yu, T.[Ting], Zhang, C.[Cha], Cohen, M.[Michael], Rui, Y.[Yong], Wu, Y.[Ying],
Monocular Video Foreground/Background Segmentation by Tracking Spatial-Color Gaussian Mixture Models,
Motion07(5-5).
IEEE DOI 0702
BibRef

Yang, S.Y.[Sheng-Yan], Hsu, C.T.[Chiou-Ting],
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency,
ICIP06(2801-2804).
IEEE DOI 0610
BibRef

Cvetkovic, S., Bakker, P., Schirris, J., de With, P.H.N.,
Background Estimation and Adaptation Model with Light-Change Removal for Heavily Down-Sampled Video Surveillance Signals,
ICIP06(1829-1832).
IEEE DOI 0610
BibRef

de Beeck, K.O., Gu, I.Y.H., Li, L.Y.[Li-Yuan], Viberg, M., de Moor, B.,
Region-Based Statistical Background Modeling for Foreground Object Segmentation,
ICIP06(3317-3320).
IEEE DOI 0610
BibRef

Chen, T.H.[Thou-Ho], Chen, T.Y.[Tsong-Yi], Chiou, Y.C.[Yung-Chuen],
An Efficient Real-Time Video Object Segmentation Algorithm Based on Change Detection and Background Updating,
ICIP06(1837-1840).
IEEE DOI 0610
BibRef

Li, R.N.[Ruo-Nan], Chen, Y.[Yu], Zhang, X.D.[Xu-Dong],
Fast Robust Eigen-Background Updating for Foreground Detection,
ICIP06(1833-1836).
IEEE DOI 0610
BibRef

Ardo, H., Berthilsson, R.,
Adaptive Background Estimation using Intensity Independent Features,
BMVC06(III:1069).
PDF File. 0609
BibRef

Shimada, A.[Atsushi], Taniguchi, R.I.[Rin-Ichiro],
Hybrid Background Model Using Spatial-Temporal LBP,
AVSBS09(19-24).
IEEE DOI 0909

See also Object Detection under Varying Illumination Based on Adaptive Background Modeling Considering Spatial Locality. BibRef

Shimada, A., Arita, D.[Daisaku], Taniguchi, R.I.[Rin-Ichiro],
Dynamic Control of Adaptive Mixture-of-Gaussians Background Model,
AVSBS06(5-5).
IEEE DOI 0611
BibRef

Chen, C.Y.[Cheng-Yao], Wolf, W.[Wayne],
Background modeling and object tracking using multi-spectral sensors,
VSSN06(27-34).
WWW Link. 0701
BibRef

Calderara, S.[Simone], Melli, R.[Rudy], Prati, A.[Andrea], Cucchiara, R.[Rita],
Reliable background suppression for complex scenes,
VSSN06(211-214).
WWW Link. 0701
BibRef

Salas, J.[Joaquín], Martínez, P.[Pedro], González, J.[Jordi],
Background Updating with the Use of Intrinsic Curves,
ICIAR06(I: 731-742).
Springer DOI 0610
BibRef

Kim, S.H.[Sung-Ho], Kim, J.H.[Jung-Ho], Park, C.[Chaehoon], Kweon, I.S.[In So],
Large object detection in cluttered background using boosted Markov Chain Monte Carlo,
ICARCV10(2096-2101).
IEEE DOI 1109
BibRef

Kim, S.H.[Sung-Ho], Yoon, K.J.[Kuk-Jin], Kweon, I.S.[In So],
Background Robust Object Labeling by Voting of Weight-Aggregated Local Features,
ICPR06(II: 219-222).
IEEE DOI 0609
BibRef

Rao, N.I.[Naveed I.], Di, H.J.[Hui-Jun], Xu, G.Y.[Guang-You],
Refine Stereo Correspondence Using Bayesian Network and Dynamic Programming on a Color Based Minimal Span Tree,
ACIVS06(610-619).
Springer DOI 0609
BibRef
And:
Joint Correspondence and Background Modeling Based on Tree Dynamic Programming,
ICPR06(II: 425-428).
IEEE DOI 0609
BibRef

Indupalli, S., Ali, M.A., Boufama, B.,
A Novel Clustering-Based Method for Adaptive Background Segmentation,
CRV06(37-37).
IEEE DOI 0607
BibRef

Singh, V.K., Maji, S., Mukerjee, A.[Amitabha],
Confidence Based updation of Motion Conspicuity in Dynamic Scenes,
CRV06(13-13).
IEEE DOI 0607
BibRef

Messelodi, S.[Stefano], Modena, C.M.[Carla Maria], Segata, N.[Nicola], Zanin, M.[Michele],
A Kalman Filter Based Background Updating Algorithm Robust to Sharp Illumination Changes,
CIAP05(163-170).
Springer DOI 0509
BibRef

Yang, L.[Lei], Yang, J.[Jie], Peng, N.S.[Ning-Song], Ling, J.G.[Jian-Guo],
Weighted Information Entropy: A Method for Estimating the Complex Degree of Infrared Images' Backgrounds,
ICIAR05(215-222).
Springer DOI 0509
BibRef

Porikli, F.M.[Fatih Murat],
Detection of temporarily static regions by processing video at different frame rates,
AVSBS07(236-241).
IEEE DOI 0709
BibRef

Porikli, F.M.[Fatih M.], Tuzel, O.[Oncel],
Bayesian background modeling for foreground detection,
VSSN05(55-58).
WWW Link. 0511
BibRef

Tuzel, O.[Oncel], Porikli, F.M., Meer, P.[Peter],
A Bayesian Approach to Background Modeling,
MVIV05(III: 58-58).
IEEE DOI 0507
BibRef

Conaire, C.O., Cooke, E., O'Connor, N.E., Murphy, N., Smearson, A.,
Background Modelling in Infrared and Visible Spectrum Video for People Tracking,
OTCBVS05(III: 20-20).
IEEE DOI 0507
BibRef

Guha, P.[Prithwijit], Palai, D.[Dibyendu], Venkatesh, K.S., Mukerjee, A.[Amitabha],
A Multiscale Co-linearity Statistic Based Approach to Robust Background Modeling,
ACCV06(I:297-306).
Springer DOI 0601
BibRef

Zhu, Q.A.[Qi-Ang], Avidan, S.[Shai], Cheng, K.T.[Kwang-Ting],
Learning a Sparse, Corner-Based Representation for Time-varying Background Modeling,
ICCV05(I: 678-685).
IEEE DOI 0510
BibRef

Le, H.[Hieu], Yu, C.P.[Chen-Ping], Zelinsky, G.J.[Gregory J.], Samaras, D.[Dimitris],
Co-localization with Category-Consistent Features and Geodesic Distance Propagation,
CEFR-LCV17(1103-1112)
IEEE DOI 1802
Detectors, Feature extraction, Kernel, Linear programming, Proposals, Training BibRef

Le, H.[Hieu], Nguyen, V.[Vu], Yu, C.P.[Chen-Ping], Samaras, D.[Dimitris],
Geodesic Distance Histogram Feature for Video Segmentation,
ACCV16(I: 275-290).
Springer DOI 1704
BibRef

Zhang, W.[Wei], Yu, B.[Bing], Zelinsky, G.J.[Gregory J.], Samaras, D.[Dimitris],
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features,
CVPR05(II: 323-330).
IEEE DOI 0507
BibRef

Yu, C.P., Le, H., Zelinsky, G.J., Samaras, D.[Dimitris],
Efficient Video Segmentation Using Parametric Graph Partitioning,
ICCV15(3155-3163)
IEEE DOI 1602
Clustering algorithms BibRef

Moreno-Noguer, F.[Francesc], Sanfeliu, A.[Alberto], Samaras, D.[Dimitris],
Integration of Conditionally Dependent Object Features for Robust Figure/Background Segmentation,
ICCV05(II: 1713-1720).
IEEE DOI 0510

See also Dependent Multiple Cue Integration for Robust Tracking.
See also Integration of deformable contours and a multiple hypotheses Fisher color model for robust tracking in varying illuminant environments. BibRef

Moreno-Noguer, F., Sanfeliu, A.,
Integration of shape and a multihypotheses fisher color model for figure-ground segmentation in non-stationary environments,
ICPR04(IV: 771-774).
IEEE DOI 0409
BibRef

Zach, C.[Christopher], Sormann, M.[Mario], Karner, K.[Konrad],
High-Performance Multi-View Reconstruction,
3DPVT06(113-120).
IEEE DOI 0606
BibRef

Alexandropoulos, T., Loumos, V., Kayafas, E.,
A block-based clustering technique for real time object detection on a static background,
ICIS04(I: 169-173).
IEEE Abstract. Refine block based extraction. BibRef 0400

Ozden, K.E., Van Gool, L.J.,
Background Recognition in Dynamic Scenes with Motion Constraints,
CVPR05(I: 250-255).
IEEE DOI 0507
BibRef

Piccurdi, M., Jan, T.,
Mean-shift background image modelling,
ICIP04(V: 3399-3402).
IEEE DOI 0505
BibRef

Yoshida, T.,
Background differencing technique for image segmentation based on the status of reference pixels,
ICIP04(V: 3487-3490).
IEEE DOI 0505
BibRef

Shao, J.[Jie], Zhou, S.K., Chellappa, R.,
Simultaneous background and foreground modeling for tracking in surveillance video,
ICIP04(II: 1053-1056).
IEEE DOI 0505
BibRef

Zhou, Y.[Yue], Xu, W.[Wei], Tao, H.[Hai], Gong, Y.H.[Yi-Hong],
Background Segmentation Using Spatial-Temporal Multi-Resolution MRF,
Motion05(II: 8-13).
IEEE DOI 0502
BibRef

Zhou, Y.[Yue], Tao, H.[Hai],
A background layer model for object tracking through occlusion,
ICCV03(1079-1085).
IEEE DOI 0311
BibRef

Tsai, Y.P.[Yu-Pao], Hung, Y.P.[Yi-Ping], Shih, Z.C.[Zen-Chung], Su, J.J.[Jin-Jen], Tsai, S.R.[Shang-Ru],
Background removal system for object movies,
ICPR04(I: 608-611).
IEEE DOI 0409
BibRef

Farin, D., de With, P.H.N., Effelsberg, W.,
Robust background estimation for complex video sequences,
ICIP03(I: 145-148).
IEEE DOI 0312
BibRef

Lee, D.S.[Dar-Shyang], Hull, J.J., Erol, B.,
A Bayesian framework for Gaussian mixture background modeling,
ICIP03(III: 973-976).
IEEE DOI 0312
BibRef

Ablavsky, V.,
Background models for tracking objects in water,
ICIP03(III: 125-128).
IEEE DOI 0312
BibRef

Cristani, M., Bicego, M., Murino, V.,
Integrated region- and pixel-based approach to background modelling,
Motion02(3-8).
IEEE DOI 0303

See also Unsupervised scene analysis: A hidden Markov model approach. BibRef

Lin, H.H.[Horng-Horng], Liu, T.L.[Tyng-Luh], Chuang, J.H.[Jen-Hui],
A probabilistic SVM approach for background scene initialization,
ICIP02(III: 893-896).
IEEE DOI 0210

See also Direct Energy Minimization for Super-Resolution on Nonlinear Manifolds. BibRef

Gustafsson, U., Haglund, L., Andersson, I.,
Target Detection and Background Suppression using Quadrature Pyramid Filters,
SCIA01(P-W5). 0206
BibRef

Harville, M.[Michael],
A Framework for High-Level Feedback to Adaptive, Per-Pixel, Mixture-of-Gaussian Background Models,
ECCV02(III: 543 ff.).
Springer DOI 0205
BibRef

Harville, M., Gordon, G.G., Woodfill, J.I.,
Adaptive Video Background Modeling Using Color and Depth,
ICIP01(III: 90-93).
IEEE DOI 0108
BibRef

Gao, D.S., Zhou, J., Xin, L.P.,
A Novel Algorithm of Adaptive Background Estimation,
ICIP01(II: 395-398).
IEEE DOI 0108
BibRef

Darrell, T.J.[Trevor J.], Demirdjian, D.[David], Checka, N.[Neal], Felzenszwalb, P.F.[Pedro F.],
Plan-View Trajectory Estimation with Dense Stereo Background Models,
ICCV01(II: 628-635).
IEEE DOI 0106
BibRef
And: MIT AI Memo-2001-001, February 2001.
WWW Link. 0105
Derive a 3-D model for the background to use in foreground tracking. BibRef

Stenger, B.[Bjoern], Ramesh, V.[Visvanathan], Paragios, N.[Nikos], Coetzee, F.[Frans], Buhmann, J.M.[Joachim M.],
Topology Free Hidden Markov Models: Application to Background Modeling,
ICCV01(I: 294-301).
IEEE DOI 0106
BibRef

Gao, X.[Xiang], Boult, T.E., Coetzee, F.[Frans], Ramesh, V.[Visvanathan],
Error Analysis of Background Adaption,
CVPR00(I: 503-510).
IEEE DOI 0005
BibRef

Rittscher, J., Kato, J., Joga, S., Blake, A.,
A Probabilistic Background Model for Tracking,
ECCV00(II: 336-350).
Springer DOI 0003
BibRef

Qian, R.J.[Richard J.], Sezan, M.I.[M. Ibrahim],
Video Background Replacement Without A Blue Screen,
ICIP99(IV:143-146).
IEEE DOI BibRef 9900

Csurka, G., Bouthemy, P.,
Direct Identification of Moving Objects and Background from 2D Motion Models,
ICCV99(566-571).
IEEE DOI BibRef 9900

Eveland, C.K.[Christopher K.], Konolige, K.G.[Kurt G.], Bolles, R.C.[Robert C.],
Background Modeling for Segmentation of Video-rate Stereo Sequences,
CVPR98(266-271).
IEEE DOI BibRef 9800

Toyama, K., Krumm, J., Brumitt, B., Meyers, B.,
Wallflower: Principles and Practice of Background Maintenance,
ICCV99(255-261).
IEEE DOI BibRef 9900

Martins, F.C.M.[Fernando C.M.], Nickerson, B.R.[Brian R.], Bostrom, V.S.[Vareck S.], Hazra, R.[Rajeeb],
Implementation of a Real-time Foreground/Background Segmentation System on the Intel Architecture,
Frame-Rate99(xx-yy).
HTML Version. BibRef 9900

Martins, I.[Isabel], Corte-Real, L.[Luís],
A video coder using 3-D model based background for video surveillance applications,
ICIP98(II: 919-923).
IEEE DOI 9810
BibRef

Chen, S., Li, Z., Zhang, G.,
A Renovated Algorithm for Extracting Moving Target from Background in Real Time Video Tracking System,
ICPR88(II: 646-648).
IEEE DOI BibRef 8800

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Foreground Object Extraction, Object Models .