19.3.4 Detection of Moving Objects from Image Sequences or Video

Lin, Y.T.[Yun-Ting], Chen, Y.K.[Yen-Kuang], Kung, S.Y.,
A Principal Component Clustering Approach to Object Oriented Motion Segmentation and Estimation,
VLSIVideo(17), No. 2-3, November 1997, pp. 163-187. 9712
BibRef
Earlier:
Object-Based Scene Segmentation Combining Motion and Image Cues,
ICIP96(I: 957-960).
IEEE DOI BibRef

Altunbasak, Y.[Yucel], Eren, P.E.[P. Erhan], Tekalp, A.M.[A. Murat],
Region-Based Parametric Motion Segmentation Using Color Information,
GMIP(60), No. 1, January 1998, pp. 13-23. BibRef 9801

Altunbasak, Y., Oten, R., and de Figueiredo, R.J.P.,
Simultaneous Object Segmentation, Multiple Object Tracking and Alpha Map Generation,
ICIP97(I: 69-72).
IEEE DOI BibRef 9700

Altunbasak, Y.[Yucel], Mersereau, R.M., Patti, A.J.[Andrew J.],
A fast parametric motion estimation algorithm with illumination and lens distortion correction,
IP(12), No. 4, April 2003, pp. 395-408.
IEEE DOI 0306
BibRef

Altunbasak, Y.[Yucel], Patti, A.J.[Andrew J.], King, O.D.[Oliver D.],
On Global Parametric Motion Estimation with Lens Distortion Correction,
ICIP99(III:686-690).
IEEE DOI BibRef 9900

Nguyen, H.T., Worring, M., Dev, A.,
Detection of Moving Objects in Video Using a Robust Motion Similarity Measure,
IP(9), No. 1, January 2000, pp. 137-141.
IEEE DOI 0001
BibRef

Onural, L.[Levent], Alatan, A.A.[Abdullah Aydin], Tuncel, E.[Ertem],
Rule-based moving object segmentation,
US_Patent6,337,917, Jan 8, 2002
WWW Link. BibRef 0201
Earlier: A2, A3, A1:
A Rule-Based Method for Object Segmentation in Video Sequences,
ICIP97(II: 522-525).
IEEE DOI BibRef

Lo, C.C.[Chi-Chun], Wang, S.J.[Shuenn-Jyi],
A histogram-based moment-preserving clustering algorithm for video segmentation,
PRL(24), No. 14, October 2003, pp. 2209-2218.
Elsevier DOI 0307
BibRef

Yang, G.B.[Gao-Bo], Yu, S.F.[Sheng-Fa],
Modified intelligent scissors and adaptive frame skipping for video object segmentation,
RealTimeImg(11), No. 4, August 2005, pp. 310-322.
Elsevier DOI 0508
BibRef

Chujoh, T.[Takeshi], Kikuchi, Y.[Yoshihiro], Sakuma, A.[Akira], Hayashi, T.[Toshifumi], Kobayashi, H.[Hiroyuki],
Method for detecting a moving object in motion video and apparatus therefor,
US_Patent6,876,701, Apr 5, 2005
WWW Link. BibRef 0504
And: US_Patent7,292,633, Nov 6, 2007
WWW Link. BibRef

Chiu, S.[Shen],
Application of Fractional Fourier Transform to Moving Target Indication via Along-Track Interferometry,
JASP(2005), No. 20, 2005, pp. 3293-3303.
WWW Link. 0603
BibRef

Gruber, A.[Amit], Weiss, Y.[Yair],
Incorporating Non-motion Cues into 3D Motion Segmentation,
CVIU(108), No. 3, December 2007, pp. 261-271.
Elsevier DOI 0711
BibRef
Earlier: ECCV06(III: 84-97).
Springer DOI 0608
BibRef
And:
Multibody factorization with uncertainty and missing data using the EM algorithm,
CVPR04(I: 707-714).
IEEE DOI 0408
3D motion segmentation, Multibody factorization, Spatial coherence, EM algorithm, Graphical models, Factor analysis, Constrained factorization; Structure from motion BibRef

Steenburgh, M.[Malcolm], Murray, D.[Don], Tucakov, V.[Vladimir], Ku, S.[Shyan], Barman, R.[Rod],
Method and apparatus for measuring dwell time of objects in an environment,
US_Patent7,167,576, Jan 23, 2007
WWW Link. BibRef 0701

Garoutte, M.V.[Maurice V.],
Video analysis using segmentation gain by area,
US_Patent7,218,756, May 15, 2007
WWW Link. BibRef 0705

Kumar, M.P.[M. Pawan], Torr, P.H.S., Zisserman, A.,
Learning Layered Motion Segmentations of Video,
IJCV(76), No. 3, March 2008, pp. 301-319.
Springer DOI 0801
BibRef
Earlier:
Learning Layered Motion Segmentation of Video,
ICCV05(I: 33-40).
IEEE DOI 0510
BibRef

Vázquez, C.[Carlos], Ghazal, M.[Mohammed], Amer, A.[Aishy],
Feature-based detection and correction of occlusions and split of video objects,
SIViP(3), No. 1, January 2009, pp. xx-yy.
Springer DOI 0902
Address occlusions and object splitting. BibRef

Li, X.[Xi], Ning, Z.N.[Zheng-Nan], Xiang, L.W.[Liu-Wei],
Robust Multi-Body Motion Segmentation Based on Fuzzy k-Subspace Clustering,
IEICE(E88-D), No. 11, November 2005, pp. 2609-2614.
DOI Link 0511

See also Robust 3D Reconstruction with Outliers Using RANSAC Based Singular Value Decomposition. BibRef

Boltz, S.[Sylvain], Herbulot, A.[Ariane], Debreuve, E.[Eric], Barlaud, M.[Michel], Aubert, G.[Gilles],
Motion and Appearance Nonparametric Joint Entropy for Video Segmentation,
IJCV(80), No. 2, November 2008, pp. xx-yy.
Springer DOI 0809
BibRef
Earlier: A2, A1, A3, A4, A5:
Space-Time Segmentation Based on a Joint Entropy with Estimation of Nonparametric Distributions,
SSVM07(721-732).
Springer DOI 0705

See also Joint Appearance and Deformable Shape for Nonparametric Segmentation.
See also High-Dimensional Statistical Measure for Region-of-Interest Tracking. BibRef

Garcia, V.[Vincent], Boltz, S.[Sylvain], Debreuve, E.[Eric], Barlaud, M.[Michel],
Outer-Layer Based Tracking using Entropy as a Similarity Measure,
ICIP07(VI: 309-312).
IEEE DOI 0709

See also Using the Shape Gradient for Active Contour Segmentation: From the Continuous to the Discrete Formulation. BibRef

Boltz, S., Wolsztynski, E., Debreuve, E., Thierry, E., Barlaud, M., Pronzato, L.,
A Minimum-Entropy Procedure for Robust Motion Estimation,
ICIP06(1249-1252).
IEEE DOI 0610
BibRef

Herbulot, A., Boltz, S., Debreuve, E., Barlaud, M.,
Robust Motion-Based Segmentation in Video Sequences using Entropy Estimator,
ICIP06(1853-1856).
IEEE DOI 0610
BibRef

Landabaso, J.L.[Jose-Luis], Pardas, M.[Montse],
A Unified Framework for Consistent 2-D/3-D Foreground Object Detection,
CirSysVideo(18), No. 8, August 2008, pp. 1040-1051.
IEEE DOI 0809
BibRef

Tsai, D.M.[Du-Ming], Chiu, W.Y.[Wei-Yao],
Motion Detection Using Fourier Image Reconstruction,
PRL(29), No. 16, 1 December 2008, pp. 2145-2155.
Elsevier DOI 0811
Motion detection, Surveillance, Foreground segmentation, Fourier transforms BibRef

Sefcik, J.[Jason],
Method and system for estimating the position of moving objects in images,
US_Patent7,277,558, Oct 2, 2007
WWW Link. BibRef 0710

Lee, J.S.[Jin Soo], Yu, J.S.[Jae Shin],
Method for extracting object region,
US_Patent7,313,254, Dec 25, 2007
WWW Link. BibRef 0712

Pan, Z.L.[Zai-Liang], Ngo, C.W.[Chong-Wah],
Moving-Object Detection, Association, and Selection in Home Videos,
MultMed(9), No. 2, February 2007, pp. 268-279.
IEEE DOI 0905
BibRef

Xu, J.F.[Jian-Feng], Yamasaki, T.[Toshihiko], Aizawa, K.[Kiyoharu],
Temporal Segmentation of 3-D Video by Histogram-Based Feature Vectors,
CirSysVideo(19), No. 6, June 2009, pp. 870-881.
IEEE DOI 0906
BibRef
Earlier:
Mutual Information in 3D Video,
3DTV07(1-4).
IEEE DOI 0705
BibRef
Earlier:
Motion Editing in 3D Video Database,
3DPVT06(472-479).
IEEE DOI 0606
BibRef
Earlier:
3D Video Segmentation Using Point Distance Histograms,
ICIP05(I: 701-704).
IEEE DOI 0512
BibRef

Yamasaki, T., Aizawa, K.,
Motion Segmentation for 3D Video Based on Spherical Registration,
3DTV07(1-4).
IEEE DOI 0705
BibRef

Celik, H.[Hasan], Hanjalic, A.[Alan], Hendriks, E.A.[Emile A.],
Unsupervised and simultaneous training of multiple object detectors from unlabeled surveillance video,
CVIU(113), No. 10, October 2009, pp. 1076-1094,.
Elsevier DOI 0910
BibRef
Earlier:
On the development of an autonomous and self-adaptable moving object detector,
AVSBS07(353-358).
IEEE DOI 0709
Object detection, Surveillance, Pattern classification, Clustering; Unsupervised learning BibRef

Celik, H.[Hasan], Hanjalic, A.[Alan], Hendriks, E.A.[Emile A.], Boughorbel, S.[Sabri],
Online training of object detectors from unlabeled surveillance video,
Learning08(1-7).
IEEE DOI 0806
BibRef

Rambabu, C.[Chinta], Kim, K.Y.[Ki-Young], Woo, W.T.[Woon-Tack],
Fast and accurate extraction of moving object silhouette for personalized Virtual Reality Studio @ Home,
RealTimeIP(4), No. 4, November 2009, pp. xx-yy.
Springer DOI 0911
VR@Home platform. Shadows and highlights using background differences in hue and saturation. BibRef

Silva da Silva, L., Scharcanski, J.[Jacob],
Video Segmentation Based on Motion Coherence of Particles in a Video Sequence,
IP(19), No. 4, April 2010, pp. 1036-1049.
IEEE DOI 1003
BibRef

Jian, Y.D.[Yong-Dian], Chen, C.S.[Chu-Song],
Two-View Motion Segmentation with Model Selection and Outlier Removal by RANSAC-Enhanced Dirichlet Process Mixture Models,
IJCV(88), No. 3, July 2010, pp. xx-yy.
Springer DOI 1003
BibRef
Earlier:
Two-View Motion Segmentation by Mixtures of Dirichlet Process with Model Selection and Outlier Removal,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Zappella, L.[Luca], Lladó, X.[Xavier], Provenzi, E., Salvi, J.[Joaquim],
Enhanced Local Subspace Affinity for feature-based motion segmentation,
PR(44), No. 2, February 2011, pp. 454-470.
Elsevier DOI 1011
BibRef
Earlier: A1, A3, A2, A4:
Adaptive Motion Segmentation Algorithm Based on the Principal Angles Configuration,
ACCV10(III: 15-26).
Springer DOI 1011
BibRef
Earlier: A1, A2, A4, Only:
Enhanced Model Selection for motion segmentation,
ICIP09(4053-4056).
IEEE DOI 0911
Motion segmentation, Manifold clustering, Model selection, Cluster number estimation BibRef

Zappella, L.[Luca], del Bue, A.[Alessio], Lladó, X.[Xavier], Salvi, J.[Joaquim],
Joint estimation of segmentation and structure from motion,
CVIU(117), No. 2, February 2013, pp. 113-129.
Elsevier DOI 1301
BibRef
Earlier:
Simultaneous motion segmentation and Structure from Motion,
WMVC11(679-684).
IEEE DOI 1101
Structure from motion, Multi-body structure from motion, Motion segmentation, Sparsity BibRef

Gay, P., Bansal, V., Rubino, C.[Cosimo], del Bue, A.[Alessio],
Probabilistic Structure from Motion with Objects (PSfMO),
ICCV17(3094-3103)
IEEE DOI 1802
CAD, cameras, image motion analysis, image sequences, object detection, principal component analysis, probability, BibRef

Magerand, L.[Ludovic], del Bue, A.[Alessio],
Revisiting Projective Structure from Motion: A Robust and Efficient Incremental Solution,
PAMI(42), No. 2, February 2020, pp. 430-443.
IEEE DOI 2001
BibRef
Earlier:
Practical Projective Structure from Motion (P2SfM),
ICCV17(39-47)
IEEE DOI 1802
Cameras, Estimation, Robustness, Image reconstruction, Structure from motion, Optimization, projective reconstruction. computational complexity, image motion analysis, least squares approximations. BibRef

Crocco, M.[Marco], Rubino, C.[Cosimo], del Bue, A.[Alessio],
Structure from Motion with Objects,
CVPR16(4141-4149)
IEEE DOI 1612
BibRef

Rubino, C.[Cosimo], Crocco, M.[Marco], Murino, V.[Vittorio], del Bue, A.[Alessio],
Semantic Multi-body Motion Segmentation,
WACV15(1145-1152)
IEEE DOI 1503
Clustering algorithms BibRef

Park, J.H.[Jong-Hyun], Cho, W.H.[Wan-Hyun], Lee, G.S.[Guee-Sang], Park, S.Y.[Soon-Young],
Moving Object Detection Based on Clausius Entropy,
IEICE(E94-D), No. 2, February 2011, pp. 388-391.
WWW Link. 1102
BibRef

Choi, J.M.[Jin-Min], Chang, H.J.[Hyung Jin], Yoo, Y.J.[Yung Jun], Choi, J.Y.[Jin Young],
Robust Moving Object Detection Against Fast Illumination Change,
CVIU(116), No. 2, February 2012, pp. 179-193.
Elsevier DOI 1201
Illumination change, Auto-exposure, Chromaticity difference model; Brightness ratio model
See also Robust and Fast Moving Object Detection in a Non-Stationary Camera Via Foreground Probability Based Sampling. BibRef

Aldroubi, A., Sekmen, A.,
Nearness to Local Subspace Algorithm for Subspace and Motion Segmentation,
SPLetters(19), No. 10, October 2012, pp. 704-707.
IEEE DOI 1209
BibRef
And: A2, A1:
Subspace and motion segmentation via local subspace estimation,
WORV13(27-33)
IEEE DOI 1307
image matching BibRef

Wei, J.[Jie],
Small Moving Object Detection from Infra-Red Sequences,
IJIG(13), No. 03, 2013, pp. 1350014.
DOI Link 1309
BibRef

Chen, Y.B.[Yi-Bin], Cai, C.H.[Can-Hui], Ma, K.K.[Kai-Kuang], Wang, X.L.[Xiao-Lan],
Layered moving-object segmentation for stereoscopic video using motion and depth information,
JVCIR(24), No. 7, 2013, pp. 829-837.
Elsevier DOI 1309
Video segmentation BibRef

Li, D.W.[Da-Wei], Xu, L.H.[Li-Hong], Goodman, E.D.,
Illumination-Robust Foreground Detection in a Video Surveillance System,
CirSysVideo(23), No. 10, 2013, pp. 1637-1650.
IEEE DOI 1311
Bayes methods BibRef

Arvanitidou, M.G.[Marina Georgia], Tok, M.[Michael], Glantz, A.[Alexander], Krutz, A.[Andreas], Sikora, T.[Thomas],
Motion-based object segmentation using hysteresis and bidirectional inter-frame change detection in sequences with moving camera,
SP:IC(28), No. 10, 2013, pp. 1420-1434.
Elsevier DOI 1312
Inter-frame change detection BibRef

Ellis, A.L.[Anna-Louise], Ferryman, J.M.[James M.],
Biologically-inspired robust motion segmentation using mutual information,
CVIU(122), No. 1, 2014, pp. 47-64.
Elsevier DOI 1404
Biologically-inspired vision BibRef

Li, L.Z.[Long-Zhen], Ellis, A.L.[Anna-Louise], Ferryman, J.M.[James M.],
On fusion for robust motion segmentation,
AVSS15(1-6)
IEEE DOI 1511
Bismuth;Entropy BibRef

Kermani, E.[Elham], Asemani, D.[Davud],
A robust adaptive algorithm of moving object detection for video surveillance,
JIVP(2014), No. 1, 2014, pp. 27.
DOI Link 1405
BibRef

Koh, E.[Eunjin], Lee, C.Y.[Chan-Young], Jeong, D.G.[Dong Gil],
Clausius Normalized Field-Based Shape-Independent Motion Segmentation,
IEICE(E97-D), No. 5, May 2014, pp. 1254-1263.
WWW Link. 1405
BibRef

Zhong, R., Hu, R., Wang, Z., Wang, S.,
Fast Synopsis for Moving Objects Using Compressed Video,
SPLetters(21), No. 7, July 2014, pp. 834-838.
IEEE DOI 1405
Algorithm design and analysis BibRef

Poling, B.[Bryan], Lerman, G.[Gilad],
A New Approach to Two-View Motion Segmentation Using Global Dimension Minimization,
IJCV(108), No. 3, July 2014, pp. 165-185.
Springer DOI 1407
Rigid body motion segmentation. Embed point correspondences in 9-D space. BibRef

Sener, O., Ugur, K., Alatan, A.A.,
Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters,
MultMed(16), No. 5, August 2014, pp. 1292-1302.
IEEE DOI 1410
filtering theory BibRef

Kang, J.W.[Jung-Won], Chung, M.J.[Myung Jin],
Fast Online Motion Segmentation through Multi-Temporal Interval Motion Analysis,
IEICE(E98-D), No. 2, February 2015, pp. 479-484.
WWW Link. 1503
BibRef

Rahmati, H.[Hodjat], Dragon, R.[Ralf], Aamo, O.M.[Ole Morten], Adde, L.[Lars], Stavdahl, Ø.[Øyvind], Van Gool, L.J.[Luc J.],
Weakly supervised motion segmentation with particle matching,
CVIU(140), No. 1, 2015, pp. 30-42.
Elsevier DOI 1509
BibRef
Earlier: A1, A2, A3, A6, A4, Only:
Motion Segmentation with Weak Labeling Priors,
GCPR14(159-171).
Springer DOI 1411
Motion segmentation BibRef

Li, H.G.[Hong-Guang], Li, X.J.[Xin-Jun], Ding, W.R.[Wen-Rui], Huang, Y.Q.[Yu-Qing],
Metadata-Assisted Global Motion Estimation for Medium-Altitude Unmanned Aerial Vehicle Video Applications,
RS(7), No. 10, 2015, pp. 12606.
DOI Link 1511
BibRef

Azzam, R., Kemouche, M.S., Aouf, N., Richardson, M.,
Efficient visual object detection with spatially global Gaussian mixture models and uncertainties,
JVCIR(36), No. 1, 2016, pp. 90-106.
Elsevier DOI 1603
Image segmentation. visual detection of moving objects using Gaussian mixture models (GMM). BibRef

Cao, X., Yang, L., Guo, X.,
Total Variation Regularized RPCA for Irregularly Moving Object Detection Under Dynamic Background,
Cyber(46), No. 4, April 2016, pp. 1014-1027.
IEEE DOI 1604
Algorithm design and analysis BibRef

Papazoglou, A.[Anestis], del Pero, L.[Luca], Ferrari, V.[Vittorio],
Discovering object aspects from video,
IVC(52), No. 1, 2016, pp. 206-217.
Elsevier DOI 1609
BibRef
And:
Video Temporal Alignment for Object Viewpoint,
ACCV16(IV: 273-288).
Springer DOI 1704
BibRef
Earlier: A1, A3, Only:
Fast Object Segmentation in Unconstrained Video,
ICCV13(1777-1784)
IEEE DOI 1403
Visual aspects. video, video segmentation
See also Behavior Discovery and Alignment of Articulated Object Classes from Unstructured Video. BibRef

Mahmoudabadi, H.[Hamid], Olsen, M.J.[Michael J.], Todorovic, S.[Sinisa],
Detecting sudden moving objects in a series of digital images with different exposure times,
CVIU(158), No. 1, 2017, pp. 17-30.
Elsevier DOI 1704
Moving object BibRef

Wang, B., Fu, Z., Xiong, H., Zheng, Y.F.,
Transductive Video Segmentation on Tree-Structured Model,
CirSysVideo(27), No. 5, May 2017, pp. 992-1005.
IEEE DOI 1705
Image segmentation, Motion segmentation, Object segmentation, Proposals, Robustness, Video sequences, Visualization, Monte Carlo approximation, parametric min-cut, temporal tree, transductive learning, video segmentation BibRef

Park, S.[Sanghyuk], Park, H.[Hyunsin], Yoo, C.D.[Chang D.],
Complex Video Scene Analysis Using Kernelized-Collaborative Behavior Pattern Learning Based on Hierarchical Representative Object Behaviors,
CirSysVideo(27), No. 6, June 2017, pp. 1275-1289.
IEEE DOI 1706
Algorithm design and analysis, Atom optics, Clustering algorithms, Collaboration, Data mining, Feature extraction, Hidden Markov models, Complex video scene analysis (VSA), kernelized-collaborative pattern learning, temporal, video segmentation BibRef

Zhang, R.G.[Rong-Guo], Liu, X.J.[Xiao-Jun], Hu, J.[Jing], Chang, K.[Kai], Liu, K.[Kun],
A fast method for moving object detection in video surveillance image,
SIViP(11), No. 5, July 2017, pp. 841-848.
Springer DOI 1706
BibRef

Freifeld, O.[Oren], Hauberg, S.[Soren], Batmanghelich, K.[Kayhan], Fisher, J.W.[John W.],
Transformations Based on Continuous Piecewise-Affine Velocity Fields,
PAMI(39), No. 12, December 2017, pp. 2496-2509.
IEEE DOI 1711
BibRef
Earlier:
Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple,
ICCV15(2911-2919)
IEEE DOI 1602
Code, Tranformations.
WWW Link. Biomedical imaging, Complexity theory, Computational modeling, Distribution functions, Histograms, Trajectory, Spatial transformations, continuous piecewise-affine velocity fields, diffeomorphisms, tessellations, priors, MCMC BibRef

Freifeld, O.[Oren], Hauberg, S.[Soren], Black, M.J.[Michael J.],
Model Transport: Towards Scalable Transfer Learning on Manifolds,
CVPR14(1378-1385)
IEEE DOI 1409
Computer Vision BibRef

Chang, J.[Jason], Wei, D.L.[Dong-Lai], Fisher, III, J.W.[John W.],
A Video Representation Using Temporal Superpixels,
CVPR13(2051-2058)
IEEE DOI 1309
oversegmentation, superpixels, supervoxels, tracking, video segmentation BibRef

Zingoni, A.[Andrea], Diani, M.[Marco], Corsini, G.[Giovanni],
A Flexible Algorithm for Detecting Challenging Moving Objects in Real-Time within IR Video Sequences,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Zhao, L., He, Z., Cao, W., Zhao, D.,
Real-Time Moving Object Segmentation and Classification From HEVC Compressed Surveillance Video,
CirSysVideo(28), No. 6, June 2018, pp. 1346-1357.
IEEE DOI 1806
Encoding, Feature extraction, Motion segmentation, Object segmentation, Streaming media, Syntactics, Tracking, video surveillance BibRef

Gangapure, V.N.[Vijay N.], Nanda, S.[Susmit], Chowdhury, A.S.[Ananda S.],
Superpixel-Based Causal Multisensor Video Fusion,
CirSysVideo(28), No. 6, June 2018, pp. 1263-1272.
IEEE DOI 1806
Low illumination, dust, smoke, shadows. Eigenvalues and eigenfunctions, Real-time systems, Streaming media, Transforms, superpixel BibRef

Gangapure, V.N.[Vijay N.], Nanda, S.[Susmit], Chowdhury, A.S.[Ananda S.], Jiang, X.Y.[Xiao-Yi],
Causal Video Segmentation Using Superseeds and Graph Matching,
GbRPR15(282-291).
Springer DOI 1511
BibRef

Sahoo, P.K., Kanungo, P., Mishra, S.,
A fast valley-based segmentation for detection of slowly moving objects,
SIViP(12), No. 7, October 2018, pp. 1265-1272.
WWW Link. 1809
BibRef

Mehta, R.[Rakesh], Amores, J.[Jaume],
Improving detection speed in video by exploiting frame correlation,
PRL(112), 2018, pp. 303-309.
Elsevier DOI 1809
BibRef

Javed, S., Mahmood, A., Al-Maadeed, S., Bouwmans, T., Jung, S.K.,
Moving Object Detection in Complex Scene Using Spatiotemporal Structured-Sparse RPCA,
IP(28), No. 2, February 2019, pp. 1007-1022.
IEEE DOI 1811
Sparse matrices, Spatiotemporal phenomena, Laplace equations, Object detection, Linear programming, Optimization, spatiotemporal regularization BibRef

Sultana, M.[Maryam], Mahmood, A.[Arif], Jung, S.K.[Soon Ki],
Unsupervised Moving Object Detection in Complex Scenes Using Adversarial Regularizations,
MultMed(23), 2021, pp. 2005-2018.
IEEE DOI 2107
Generative adversarial networks, Lighting, Heuristic algorithms, Object detection, Minimization, generative adversarial networks BibRef

Shijila, B., Tom, A.J.[Anju Jose], George, S.N.[Sudhish N.],
Moving object detection by low rank approximation and L1-TV regularization on RPCA framework,
JVCIR(56), 2018, pp. 188-200.
Elsevier DOI 1811
Moving object detection, Low rank recovery, Background subtraction, Robust principle component analysis BibRef

Li, L.H.[Lin-Hao], Hu, Q.H.[Qing-Hua], Li, X.[Xin],
Moving Object Detection in Video via Hierarchical Modeling and Alternating Optimization,
IP(28), No. 4, April 2019, pp. 2021-2036.
IEEE DOI 1901
image motion analysis, image resolution, Markov processes, object detection, optimisation, video signal processing, alternating direction multipliers method (ADMM) BibRef

Kandylakis, Z.[Zacharias], Vasili, K.[Konstantinos], Karantzalos, K.[Konstantinos],
Fusing Multimodal Video Data for Detecting Moving Objects/Targets in Challenging Indoor and Outdoor Scenes,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Tom, A.J., George, S.N.,
Video Completion and Simultaneous Moving Object Detection for Extreme Surveillance Environments,
SPLetters(26), No. 4, April 2019, pp. 577-581.
IEEE DOI 1903
TV, Surveillance, Minimization, Video sequences, Object detection, Cleaning, Tensor low rank approximation, moving object detection, half thresholding BibRef

Tom, A.J., George, S.N.,
Simultaneous Reconstruction and Moving Object Detection From Compressive Sampled Surveillance Videos,
IP(29), 2020, pp. 7590-7602.
IEEE DOI 2007
Low rank approximation, 3D anisotropic total variation, moving object detection, compressed sensing BibRef

Chen, B., Shi, L., Ke, X.,
A Robust Moving Object Detection in Multi-Scenario Big Data for Video Surveillance,
CirSysVideo(29), No. 4, April 2019, pp. 982-995.
IEEE DOI 1904
Object detection, Robustness, Sparse matrices, Video surveillance, Video sequences, Context modeling, Big data, mutiple scenarios, moving object detection BibRef

Kanojia, G.[Gagan], Raman, S.[Shanmuganathan],
Patch-based detection of dynamic objects in CrowdCam images,
VC(35), No. 4, April 2019, pp. 521-534.
Springer DOI 1906
static and dynamic parts of scene. BibRef

Ma, Y.[Yuchi], Anderson, J.[John], Crouch, S.[Stephen], Shan, J.[Jie],
Moving Object Detection and Tracking with Doppler LiDAR,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Minaee, S.[Shervin], Wang, Y.[Yao],
An ADMM Approach to Masked Signal Decomposition Using Subspace Representation,
IP(28), No. 7, July 2019, pp. 3192-3204.
IEEE DOI 1906
image matching, image reconstruction, image representation, motion estimation, object detection, optimisation, segmentation BibRef

Guo, Z.M.[Zi-Ming], Cai, B.G.[Bai-Gen], Jiang, W.[Wei], Wang, J.[Jian],
Feature-based detection and classification of moving objects using LiDAR sensor,
IET-ITS(13), No. 7, July 2019, pp. 1088-1096.
DOI Link 1906
BibRef

Zhou, Y.[Yang], Ling, B.W.K.[Bingo Wing-Kuen],
Detecting moving objects via the low-rank representation,
SIViP(13), No. 8, November 2019, pp. 1593-1601.
WWW Link. 1911
BibRef

Isik, S.[Sahin], Özkan, K.[Kemal], Gerek, Ö.N.[Ömer Nezih],
CVABS: moving object segmentation with common vector approach for videos,
IET-CV(13), No. 8, December 2019, pp. 719-729.
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Compressed Domain Moving Object Detection Based on CRF,
CirSysVideo(30), No. 3, March 2020, pp. 674-684.
IEEE DOI 2003
Standards, Feature extraction, Encoding, Video sequences, Object detection, Complexity theory, Data mining, moving object BibRef

Fujimura, Y.[Yuki], Sonogashira, M.[Motoharu], Iiyam, M.[Masaaki],
Simultaneous Estimation of Object Region and Depth in Participating Media Using a ToF Camera,
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Object Detection in Videos by High Quality Object Linking,
PAMI(42), No. 5, May 2020, pp. 1272-1278.
IEEE DOI 2004
Object detection in videos, object linking BibRef

Kanojia, G., Raman, S.,
Simultaneous Detection and Removal of Dynamic Objects in Multi-view Images,
WACV20(1979-1988)
IEEE DOI 2006
Heuristic algorithms, Vehicle dynamics, Videos, Feature extraction, Cameras, Task analysis, Dynamics BibRef

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Texture collinearity foreground segmentation for night videos,
CVIU(200), 2020, pp. 103032.
Elsevier DOI 2010
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Bio-inspired Boosting for Moving Objects Segmentation,
ICIAR16(397-406).
Springer DOI 1608
Background subtraction, Foreground segmentation, Change detection, GMM, MOG, Night videos, Texture features, Texture matching BibRef

Jin, R.B.[Rui-Bing], Lin, G.S.[Guo-Sheng], Wen, C.Y.[Chang-Yun], Wang, J.L.[Jian-Liang],
Motion Context Network for Weakly Supervised Object Detection in Videos,
SPLetters(27), 2020, pp. 1864-1868.
IEEE DOI 2011
Correlation, Optical imaging, Videos, Optical signal processing, Integrated optics, Feature extraction, Object detection, weakly supervised learning BibRef

Fute, E.T.[Elie Tagne], Deffo, L.L.S.[Lionel Landry Sop], Tonye, E.[Emmanuel],
HADEM-MACS: a hybrid approach for detection and extraction of objects in movement by multimedia autonomous computer systems,
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Wang, C.J.[Chen-Jie], Li, C.Y.[Cheng-Yuan], Liu, J.[Jun], Luo, B.[Bin], Su, X.[Xin], Wang, Y.J.[Ya-Jun], Gao, Y.[Yan],
U2-ONet: A Two-Level Nested Octave U-Structure Network with a Multi-Scale Attention Mechanism for Moving Object Segmentation,
RS(13), No. 1, 2021, pp. xx-yy.
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Zou, C.[Cheng], He, B.W.[Bing-Wei], Zhu, M.Z.[Ming-Zhu], Zhang, L.W.[Li-Wei], Zhang, J.W.[Jian-Wei],
Encode-decode network with fully connected CRF for dynamic objects detection and static maps reconstruction,
SP:IC(95), 2021, pp. 116237.
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Robot vision, Encode-decode network, CRF, Dynamic objects detection, Static maps reconstruction BibRef

Yi, R.[Ran], Ye, Z.P.[Zi-Peng], Zhao, W.[Wang], Yu, M.J.[Min-Jing], Lai, Y.K.[Yu-Kun], Liu, Y.J.[Yong-Jin],
Feature-Aware Uniform Tessellations on Video Manifold for Content-Sensitive Supervoxels,
PAMI(43), No. 9, September 2021, pp. 3183-3195.
IEEE DOI 2108
BibRef
Earlier: A1, A6, A5, Only:
Content-Sensitive Supervoxels via Uniform Tessellations on Video Manifolds,
CVPR18(646-655)
IEEE DOI 1812
Voxels, coherent in apprarance and motion. Streaming media, Manifolds, Cascading style sheets, Spatiotemporal phenomena, Color, centroidal Voronoi tessellation. Manifolds, Image color analysis, Generators, BibRef

Cai, Q.[Qi], Chen, Z.F.[Zhi-Feng], Wu, D.P.O.[Da-Peng Oliver], Liu, S.[Shan], Li, X.[Xiang],
A Novel Video Coding Strategy in HEVC for Object Detection,
CirSysVideo(31), No. 12, December 2021, pp. 4924-4937.
IEEE DOI 2112
Video coding, Object detection, Bit rate, Encoding, Codecs, Detectors, Visualization, HEVC, object detection, detection accuracy modeling, bit allocation BibRef

Gao, F.[Fei], Li, Y.Y.[Yun-Yang], Lu, S.F.[Shu-Fang],
Extracting Moving Objects More Accurately: A CDA Contour Optimizer,
CirSysVideo(31), No. 12, December 2021, pp. 4840-4849.
IEEE DOI 2112
Change detection algorithms, Image edge detection, Feature extraction, Unsupervised learning, Supervised learning, motion detection BibRef

Mondal, A.[Anindya], Shashant, R., Giraldo, J.H.[Jhony H.], Bouwmans, T.[Thierry], Chowdhury, A.S.[Ananda S.],
Moving Object Detection for Event-based Vision using Graph Spectral Clustering,
GSP-CV21(876-884)
IEEE DOI 2112
Visualization, Neuromorphics, Object detection, Vision sensors, Semisupervised learning, Cameras BibRef

Giraldo, J.H.[Jhony H.], Javed, S.[Sajid], Werghi, N.[Naoufel], Bouwmans, T.[Thierry],
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos,
RSLCV21(225-233)
IEEE DOI 2112
Deep learning, Training, Video sequences, Supervised learning, Pipelines, Object detection BibRef

Feng, J.[Junyi], Li, S.Y.[Song-Yuan], Li, X.[Xi], Wu, F.[Fei], Tian, Q.[Qi], Yang, M.H.[Ming-Hsuan], Ling, H.B.[Hai-Bin],
TapLab: A Fast Framework for Semantic Video Segmentation Tapping Into Compressed-Domain Knowledge,
PAMI(44), No. 3, March 2022, pp. 1591-1603.
IEEE DOI 2202
Image segmentation, Semantics, Streaming media, Motion segmentation, Real-time systems, Task analysis, compressed domain BibRef

Arrigoni, F.[Federica], Ricci, E.[Elisa], Pajdla, T.[Tomas],
Multi-frame Motion Segmentation by Combining Two-Frame Results,
IJCV(130), No. 3, March 2022, pp. 696-728.
Springer DOI 2203
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Arrigoni, F.[Federica], Magri, L.[Luca], Pajdla, T.[Tomas],
On the Usage of the Trifocal Tensor in Motion Segmentation,
ECCV20(XX:514-530).
Springer DOI 2011
BibRef
Earlier: A1, A3, Only:
Robust Motion Segmentation From Pairwise Matches,
ICCV19(671-681)
IEEE DOI 2004
image matching, image motion analysis, image segmentation, pairwise matches, Structure from motion BibRef

Mustafa, A.[Armin], Russell, C.[Chris], Hilton, A.[Adrian],
4D Temporally Coherent Multi-Person Semantic Reconstruction and Segmentation,
IJCV(130), No. 6, June 2022, pp. 1583-1606.
Springer DOI 2207
BibRef
Earlier:
U4D: Unsupervised 4D Dynamic Scene Understanding,
ICCV19(10422-10431)
IEEE DOI 2004
image motion analysis, image reconstruction, image segmentation, image sequences, object detection, pose estimation, Estimation BibRef

Dai, P.W.[Peng-Wen], Yao, S.Y.[Si-Yuan], Li, Z.[Zekun], Zhang, S.[Sanyi], Cao, X.C.[Xiao-Chun],
ACE: Anchor-Free Corner Evolution for Real-Time Arbitrarily-Oriented Object Detection,
IP(31), 2022, pp. 4076-4089.
IEEE DOI 2206
Object detection, Image segmentation, Task analysis, Semantics, Proposals, Location awareness, Visualization, Object detection, evolution BibRef

Wang, D.[Degen], Wang, T.[Tong], Cui, W.C.[Wei-Chen], Liu, C.[Cheng],
Adaptive Support-Driven Sparse Recovery STAP Method with Subspace Penalty,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
STAP: Space-Time Adaptive Processing. BibRef

You, M.Y.[Ming-Yu], Luo, C.X.[Chao-Xian], Zhou, H.J.[Hong-Jun], Zhu, S.Q.[Shao-Qing],
Dynamic dense CRF inference for video segmentation and semantic SLAM,
PR(133), 2023, pp. 109023.
Elsevier DOI 2210
Incremental multi-class video segmentation, Semantic robotSimultaneous Localization and mMapping, Dynamic dense conditional random field BibRef

Haller, E.[Emanuela], Florea, A.M.[Adina Magda], Leordeanu, M.[Marius],
Iterative Knowledge Exchange Between Deep Learning and Space-Time Spectral Clustering for Unsupervised Segmentation in Videos,
PAMI(44), No. 11, November 2022, pp. 7638-7656.
IEEE DOI 2210
Videos, Clustering algorithms, Task analysis, Object segmentation, Mathematical models, Deep learning, Convergence, deep learning BibRef

Marcu, A.[Alina], Licaret, V.[Vlad], Costea, D.[Dragos], Leordeanu, M.[Marius],
Semantics Through Time: Semi-supervised Segmentation of Aerial Videos with Iterative Label Propagation,
ACCV20(I:537-552).
Springer DOI 2103
BibRef

Yuan, S.R.[Shu-Rong], Shi, L.[Lei], Yao, B.[Bo], Zhai, Y.T.[Yu-Tong], Li, F.Y.[Fang-Yan], Du, Y.F.[Yue-Fan],
Detection of the New Class of Hypersonic Targets under Emerging Hyperspectral Sample Streams: An Unsupervised Isolation Forest Solution,
RS(14), No. 20, 2022, pp. xx-yy.
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An, Z.J.[Zi-Jia], Liu, C.L.[Chun-Lei], Han, Y.Q.[Yu-Qi],
Effectiveness Guided Cross-Modal Information Sharing for Aligned RGB-T Object Detection,
SPLetters(29), 2022, pp. 2562-2566.
IEEE DOI 2301
Feature extraction, Information sharing, Correlation, Interference, Object detection, Data mining, Visualization, modal effectiveness guiding BibRef

Li, X.M.[Xiao-Min], Nabati, R.[Ramin], Singh, K.[Kunjan], Corona, E.[Enrique], Metsis, V.[Vangelis], Parchami, A.[Armin],
EMOD: Efficient Moving Object Detection via Image Eccentricity Analysis and Sparse Neural Networks,
RealWorld23(51-59)
IEEE DOI 2302
Convolution, Computational modeling, Pipelines, Object detection, Object segmentation, Streaming media, Cameras BibRef

Sabat, N.[Neelesh], Subodh-Raj, M.S., George, S.N.[Sudhish N.], Kumar, T.K. .S.I.[T.K. Sun-Il],
A computationally efficient moving object detection technique using tensor QR decomposition based TRPCA framework,
JVCIR(92), 2023, pp. 103785.
Elsevier DOI 2303
Moving object detection, Tensor QR decomposition, Robust principal component analysis, Half thresholding BibRef

Xu, B.T.[Bi-Tong], Li, Z.Z.[Zheng-Zhou], Cheng, B.[Bei], Yang, Y.X.[Yu-Xin], Siddique, A.[Abubakar],
A Target Imaging and Recognition Method Based on Raptor Vision,
RS(15), No. 8, 2023, pp. 2106.
DOI Link 2305
Based on wide field of view and high-resolution (fovea) of raptors. BibRef

Liang, C.[Chen], Wang, W.G.[Wen-Guan], Zhou, T.F.[Tian-Fei], Miao, J.X.[Jia-Xu], Luo, Y.[Yawei], Yang, Y.[Yi],
Local-Global Context Aware Transformer for Language-Guided Video Segmentation,
PAMI(45), No. 8, August 2023, pp. 10055-10069.
IEEE DOI 2307
Transformers, Task analysis, Visualization, Linguistics, Object segmentation, Grounding, multi-modal transformer BibRef

Xu, B.W.[Bang-Wu], Wu, Q.[Qin], Chai, Z.L.[Zhi-Lei], Guo, X.L.[Xue-Liang], Shi, J.B.[Jian-Bo],
GAMA: Geometric analysis based motion-aware architecture for moving object segmentation,
CVIU(234), 2023, pp. 103751.
Elsevier DOI 2307
Moving object segmentation, Motion degeneracy, Geometric analysis, Bidirectional motion constraint, Motion-aware architecture BibRef

Liu, H.[Hao], Ma, Y.[Yanni], Wang, H.[Hanyun], Zhang, C.[Chaobo], Guo, Y.L.[Yu-Lan],
AnchorPoint: Query Design for Transformer-Based 3D Object Detection and Tracking,
ITS(24), No. 10, October 2023, pp. 10988-11000.
IEEE DOI 2310
BibRef

Zhou, B.[Benjia], Wang, P.[Pichao], Wan, J.[Jun], Liang, Y.Y.[Yan-Yan], Wang, F.[Fan],
A Unified Multimodal De- and Re-Coupling Framework for RGB-D Motion Recognition,
PAMI(45), No. 10, October 2023, pp. 11428-11442.
IEEE DOI 2310
BibRef

Park, C.H.[Chee-Hyun], Chang, J.H.[Joon-Hyuk],
Robust Time-of-Arrival-Based Splitting Mean Moving Object Localization,
SPLetters(31), 2024, pp. 226-230.
IEEE DOI 2401
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Dong, G.F.[Guan-Fang], Zhao, C.Q.[Chen-Qiu], Pan, X.C.[Xi-Chen], Basu, A.[Anup],
Learning Temporal Distribution and Spatial Correlation Toward Universal Moving Object Segmentation,
IP(33), 2024, pp. 2447-2461.
IEEE DOI Code:
WWW Link. 2404
Videos, Training, Object segmentation, Correlation, Iterative methods, Mathematical models, Deep learning, machine learning BibRef

Panigrahi, U.[Upasana], Sahoo, P.K.[Prabodh Kumar], Panda, M.K.[Manoj Kumar], Panda, G.[Ganapati],
A ResNet-101 deep learning framework induced transfer learning strategy for moving object detection,
IVC(146), 2024, pp. 105021.
Elsevier DOI 2405
Background subtraction, Deep learning architecture, Transfer learning, Feature pooling framework, Contrast normalization BibRef

Zeng, C.[Can], Qiao, Y.L.[Yu-Long],
A Moving Object Detection Method Based on Graph Neural Network,
CVIDL23(549-554)
IEEE DOI 2403
Optical filters, Motion segmentation, Heuristic algorithms, Object detection, Feature extraction, Prediction algorithms, GraphSAGE BibRef

Yu, J.W.[Jiang-Wei], Li, X.[Xiang], Zhao, X.R.[Xin-Ran], Zhang, H.M.[Hong-Ming], Wang, Y.X.[Yu-Xiong],
Video State-Changing Object Segmentation,
ICCV23(20382-20391)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, X.T.[Xiang-Tai], Yuan, H.[Haobo], Zhang, W.W.[Wen-Wei], Cheng, G.L.[Guang-Liang], Pang, J.M.[Jiang-Miao], Loy, C.C.[Chen Change],
Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation,
ICCV23(13877-13887)
IEEE DOI Code:
WWW Link. 2401
BibRef

Homeyer, C.[Christian], Schnörr, C.[Christoph],
On Moving Object Segmentation from Monocular Video with Transformers,
NIVT23(880-891)
IEEE DOI 2401
BibRef

Liu, H.S.[Hai-Song], Teng, Y.[Yao], Lu, T.[Tao], Wang, H.[Haiguang], Wang, L.M.[Li-Min],
SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos,
ICCV23(18534-18544)
IEEE DOI Code:
WWW Link. 2401
BibRef

Ding, H.H.[Heng-Hui], Liu, C.[Chang], He, S.T.[Shu-Ting], Jiang, X.D.[Xu-Dong], Loy, C.C.[Chen Change],
MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions,
ICCV23(2694-2703)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cheng, H.K.[Ho Kei], Oh, S.W.[Seoung Wug], Price, B.[Brian], Schwing, A.[Alexander], Lee, J.Y.[Joon-Young],
Tracking Anything with Decoupled Video Segmentation,
ICCV23(1316-1326)
IEEE DOI 2401
BibRef

Fan, K.[Ke], Lei, J.[Jingshi], Qian, X.[Xuelin], Yu, M.[Miaopeng], Xiao, T.J.[Tian-Jun], He, T.[Tong], Zhang, Z.[Zheng], Fu, Y.W.[Yan-Wei],
Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation,
ICCV23(1272-1281)
IEEE DOI Code:
WWW Link. 2401
BibRef

Bekuzarov, M.[Maksym], Bermudez, A.[Ariana], Lee, J.Y.[Joon-Young], Li, H.[Hao],
XMem++: Production-level Video Segmentation From Few Annotated Frames,
ICCV23(635-644)
IEEE DOI Code:
WWW Link. 2401
BibRef

Prummel, W.[Wieke], Giraldo, J.H.[Jhony H.], Zakharova, A.[Anastasia], Bouwmans, T.[Thierry],
Inductive Graph Neural Networks for Moving Object Segmentation,
ICIP23(2730-2734)
IEEE DOI 2312
BibRef

Lian, L.[Long], Wu, Z.R.[Zhi-Rong], Yu, S.X.[Stella X.],
Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping,
CVPR23(14582-14591)
IEEE DOI 2309
BibRef

Kumar, N.[Nishant], Šegvic, S.[Siniša], Eslami, A.[Abouzar], Gumhold, S.[Stefan],
Normalizing Flow based Feature Synthesis for Outlier-Aware Object Detection,
CVPR23(5156-5165)
IEEE DOI 2309
BibRef

Lin, Z.H.[Zhi-Hao], Wang, Y.T.[Yong-Tao], Zhang, J.[Jinhe], Chu, X.J.[Xiao-Jie],
DynamicDet: A Unified Dynamic Architecture for Object Detection,
CVPR23(6282-6291)
IEEE DOI 2309
BibRef

Wang, T.[Tao],
Learning to Detect and Segment for Open Vocabulary Object Detection,
CVPR23(7051-7060)
IEEE DOI 2309
BibRef

Yu, T.T.[Ting-Ting], Chen, C.[Chen], Zhou, Y.C.[Yi-Chao], Hu, X.Y.[Xi-Yuan],
Improving Surveillance Object Detection with Adaptive Omni-attention over Both Inter-frame and Intra-frame Context,
ACCV22(II:222-237).
Springer DOI 2307
BibRef

Pavlitskaya, S.[Svetlana], Polley, N.[Nikolai], Weber, M.[Michael], Zöllner, J.M.[J. Marius],
Adversarial Vulnerability of Temporal Feature Networks for Object Detection,
SafeDrive22(510-525).
Springer DOI 2304
BibRef

Lee, J.K.[Jun-Kyu], Varghese, B.[Blesson], Vandierendonck, H.[Hans],
ROMA: Run-Time Object Detection To Maximize Real-Time Accuracy,
WACV23(6394-6403)
IEEE DOI 2302
Histograms, Analytical models, Runtime, Detectors, Object detection, Switches, Applications: Embedded sensing/real-time techniques BibRef

Griffin, B.[Brent],
Mobile Robot Manipulation using Pure Object Detection,
WACV23(561-571)
IEEE DOI 2302

WWW Link. Visualization, Annotations, Robot vision systems, Estimation, Object detection, Benchmark testing, Mobile robots, Vision + language and/or other modalities BibRef

Kreutz, T.[Thomas], Mühlhäuser, M.[Max], Guinea, A.S.[Alejandro Sanchez],
Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series,
WACV23(1644-1653)
IEEE DOI 2302
Point cloud compression, Laser radar, Annotations, Time series analysis, Neural networks, Clustering algorithms BibRef

Belharbi, S.[Soufiane], Ben Ayed, I.[Ismail], McCaffrey, L.[Luke], Granger, E.[Eric],
TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos,
WACV23(137-146)
IEEE DOI 2302
Location awareness, Training, Visualization, Streaming media, Parallel processing, Real-time systems, Proposals, un-supervised learning BibRef

Guo, Y.L.[Yu-Lan], Yin, Q.[Qian], Hu, Q.Y.[Qing-Yong], Zhang, F.[Feng], Xiao, C.[Chao], Zhang, Y.[Ye], Wang, H.[Hanyun], Dai, C.G.[Chen-Guang], Yang, J.[Jian], Zhou, Z.[Zhuang], Guo, W.L.[Wei-Long], Qi, X.[Xiyu], Tu, K.[Kelong], Xu, C.[Cong], Zhu, S.[Shudan], Chen, L.[Lai], Lin, B.[Bin], Xue, C.[Chaocan], Zheng, J.L.[Jin-Lei], Qin, L.[Limei], Li, Y.[Ying], Zhao, M.[Manqi], Ruan, L.[Lu], Cui, M.P.[Ming-Peng], Ding, G.C.[Guan-Chen], Jiang, G.[Guangwei], Chen, Z.Z.[Zhen-Zhong], Sun, Y.H.[Yu-Han], Cao, K.Y.[Kai-Yang], Kong, L.Y.[Ling-Yu], Chen, S.D.[Shao-Dong], Zhao, Z.C.[Zhi-Cheng], Shen, Q.[Qin], Liu, L.[Lei], Li, C.L.[Cheng-Long], Xiao, Y.[Yun],
The First Challenge on Moving Object Detection and Tracking in Satellite Videos: Methods and Results,
ICPR22(4981-4988)
IEEE DOI 2212
Satellites, Object detection, Benchmark testing, Object tracking, Videos BibRef

Ozbay, B.[Bengisu], Camps, O.[Octavia], Sznaier, M.[Mario],
Fast Two-View Motion Segmentation Using Christoffel Polynomials,
ECCV22(XXX:1-19).
Springer DOI 2211
BibRef

Osman, I.[Islam], Shehata, M.S.[Mohamed S.],
Few-Shot Learning Network for Moving Object Detection Using Exemplar-Based Attention Map,
ICIP22(1056-1060)
IEEE DOI 2211
Deep learning, Object detection, Benchmark testing, Task analysis, Videos, Few-shot learning, meta-learning, moving object detection, deep learning BibRef

García-González, J.[Jorge], Luque-Baena, R.M.[Rafael M.], Ortiz-de-Lazcano-Lobato, J.M.[Juan M.], López-Rubio, E.[Ezequiel],
Moving Object Detection in Noisy Video Sequences Using Deep Convolutional Disentangled Representations,
ICIP22(1376-1380)
IEEE DOI 2211
Training, Image segmentation, Shape, Video sequences, Object detection, Probabilistic logic, Proposals, Autoencoders BibRef

Köksal, A.[Aybora], Tuzcuoglu, Ö.[Önder], Ince, K.G.[Kutalmis Gökalp], Ataseven, Y.[Yoldas], Alatan, A.A.[A. Aydin],
Improved Hard Example Mining Approach for Single Shot Object Detectors,
ICIP22(3536-3540)
IEEE DOI 2211
Training, Detectors, Object detection, Real-time systems, hard example mining, loss rank mining, real time object detection BibRef

Kim, D.[Dahun], Xie, J.[Jun], Wang, H.Y.[Hui-Yu], Qiao, S.Y.[Si-Yuan], Yu, Q.H.[Qi-Hang], Kim, H.S.[Hong-Seok], Adam, H.[Hartwig], Kweon, I.S.[In So], Chen, L.C.[Liang-Chieh],
TubeFormer-DeepLab: Video Mask Transformer,
CVPR22(13904-13914)
IEEE DOI 2210
Semantics, Predictive models, Benchmark testing, Transformers, Electron tubes, grouping and shape analysis BibRef

Park, Y.[Younghyun], Kim, S.[Soyeong], Choi, W.[Wonjeong], Han, D.J.[Dong-Jun], Moon, J.[Jaekyun],
Active Object Detection with Epistemic Uncertainty and Hierarchical Information Aggregation,
ECV22(2711-2715)
IEEE DOI 2210
Training, Measurement, Learning systems, Uncertainty, Head, Computational modeling, Object detection BibRef

Du, X.F.[Xue-Feng], Wang, X.[Xin], Gozum, G.[Gabriel], Li, Y.X.[Yi-Xuan],
Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild,
CVPR22(13668-13678)
IEEE DOI 2210
Training, Uncertainty, Shape, Object detection, Predictive models, Pattern recognition, Reliability, Transparency, fairness, retrieval BibRef

Yang, B.B.[Bin-Bin], Deng, X.C.[Xin-Chi], Shi, H.[Han], Li, C.L.[Chang-Lin], Zhang, G.W.[Geng-Wei], Xu, H.[Hang], Zhao, S.[Shen], Lin, L.[Liang], Liang, X.D.[Xiao-Dan],
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism,
CVPR22(9245-9254)
IEEE DOI 2210
Correlation, Prototypes, Object detection, Logic gates, Streaming media, Pattern recognition, retrieval BibRef

Fu, Q.C.[Qi-Chen], Liu, X.Y.[Xing-Yu], Kitani, K.M.[Kris M.],
Sequential Voting with Relational Box Fields for Active Object Detection,
CVPR22(2364-2373)
IEEE DOI 2210
Supervised learning, Stochastic processes, Estimation, Reinforcement learning, Object detection, Pattern recognition, retrieval BibRef

Shen, Y.C.[Yi-Chun], Jiang, W.L.[Wan-Li], Xu, Z.[Zhen], Li, R.D.[Run-Dong], Kwon, J.H.[Jung-Hyun],
Confidence Propagation Cluster: Unleash Full Potential of Object Detectors,
CVPR22(1141-1151)
IEEE DOI 2210
Message passing, Robot vision systems, Detectors, Object detection, Parallel processing, Pattern recognition, Recognition: detection, Video analysis and understanding BibRef

Xu, R.[Ran], Mu, F.Z.[Fang-Zhou], Lee, J.[Jayoung], Mukherjee, P.[Preeti], Chaterji, S.[Somali], Bagchi, S.[Saurabh], Li, Y.[Yin],
Smartadapt: Multi-branch Object Detection Framework for Videos on Mobiles,
CVPR22(2518-2528)
IEEE DOI 2210
Schedules, Runtime, Machine learning algorithms, Tracking, Machine vision, Object detection, Machine learning, retrieval BibRef

Hu, J.Y.[Ji-Yuan], Wang, T.[Tao], Zhu, S.Q.[Shi-Qiang],
VMM: Viewpoint-based Memory Mechanism for Object Detection of Moving Sensors,
ISCV22(1-7)
IEEE DOI 2208
Performance evaluation, Location awareness, Costs, Virtual machine monitors, Detectors, Object detection. BibRef

Fujitake, M.[Masato], Sugimoto, A.[Akihiro],
Video representation learning through prediction for online object detection,
RWSurvil22(530-539)
IEEE DOI 2202
Representation learning, Conferences, Stochastic processes, Object detection, Detectors, Streaming media, Predictive models BibRef

Cores, D.[Daniel], Brea, V.M.[Víctor M.], Mucientes, M.[Manuel],
Spatio-Temporal Object Detection from UAV On-Board Cameras,
CAIP21(II:143-152).
Springer DOI 2112
BibRef

Yang, G.S.[Geng-Shan], Ramanan, D.[Deva],
Learning to Segment Rigid Motions from Two Frames,
CVPR21(1266-1275)
IEEE DOI 2111
Motion segmentation, Motion estimation, Estimation, Training data, Computer architecture BibRef

Hu, Y.T.[Yuan-Ting], Wang, J.H.[Jia-Hong], Yeh, R.A.[Raymond A.], Schwing, A.G.[Alexander G.],
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data,
CVPR21(1418-1428)
IEEE DOI 2111
BibRef
And: HVU21(3359-3369)
IEEE DOI 2109
Solid modeling, Annotations, Object detection, Data models BibRef

Psaltis, A.[Athanasios], Dimou, A.[Anastasios], Alvarez, F.[Federico], Daras, P.[Petros],
Flow R-CNN: Flow-enhanced Object Detection,
CADL20(685-700).
Springer DOI 2103
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Javed, S., Mahmood, A., Dias, J., Werghi, N.,
CS-RPCA: Clustered Sparse RPCA for Moving Object Detection,
ICIP20(3209-3213)
IEEE DOI 2011
Sparse matrices, Feature extraction, Manifolds, Matrix decomposition, Linear programming, Computational modeling, Robust PCA BibRef

Roy, S.M., Bouwmans, T.,
Dual Information-Based Background Model For Moving Object Detection,
ICIP20(3219-3223)
IEEE DOI 2011
Hidden Markov models, Histograms, Object detection, Adaptation models, Computational modeling, Video sequences, complex backgrounds BibRef

Constantinou, G.[George], You, S.[Suya], Shahabi, C.[Cyrus],
Towards Scalable and Efficient Client Selection for Federated Object Detection,
ICPR22(5140-5146)
IEEE DOI 2212
Training, Deep learning, Privacy, Federated learning, Neural networks, Object detection BibRef

Constantinou, G., Shahabi, C., Kim, S.H.,
Spatial Keyframe Extraction Of Mobile Videos For Efficient Object Detection At The Edge,
ICIP20(1466-1470)
IEEE DOI 2011
Videos, Cameras, Metadata, Image edge detection, Silicon, Visualization, Object detection, spatial keyframe extraction, object detection BibRef

Brazil, G.[Garrick], Pons-Moll, G.[Gerard], Liu, X.M.[Xiao-Ming], Schiele, B.[Bernt],
Kinematic 3d Object Detection in Monocular Video,
ECCV20(XXIII:135-152).
Springer DOI 2011
BibRef

Du, L., Ye, X., Tan, X., Feng, J., Xu, Z., Ding, E., Wen, S.,
Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection,
CVPR20(13326-13335)
IEEE DOI 2008
Feature extraction, Object detection, Solid modeling, Adaptation models, Robustness, Proposals BibRef

Amrani, E., Ben-Ari, R., Shapira, I., Hakim, T., Bronstein, A.M.,
Self-Supervised Object Detection and Retrieval Using Unlabeled Videos,
MULWS20(4100-4108)
IEEE DOI 2008
Videos, Object detection, Noise measurement, Training, Detectors, Manuals, Visualization BibRef

Mandal, M., Kumar, L.K., Saran, M.S.[M. Singh], Vipparthi, S.K.,
MotionRec: A Unified Deep Framework for Moving Object Recognition,
WACV20(2723-2732)
IEEE DOI 2006
Feature extraction, Videos, Object detection, Detectors, History, Estimation, Task analysis BibRef

Chai, Y.,
Patchwork: A Patch-Wise Attention Network for Efficient Object Detection and Segmentation in Video Streams,
ICCV19(3414-3423)
IEEE DOI 2004
image motion analysis, image segmentation, learning (artificial intelligence), object detection, History BibRef

Amrani, E., Ben-Ari, R., Hakim, T., Bronstein, A.M.,
Learning to Detect and Retrieve Objects From Unlabeled Videos,
MMVAMTC19(3713-3717)
IEEE DOI 2004
correlation methods, feature extraction, object detection, pattern clustering, supervised learning, video retrieval, Task analysis BibRef

Dave, A., Tokmakov, P., Ramanan, D.,
Towards Segmenting Anything That Moves,
HVU19(1493-1502)
IEEE DOI 2004
image motion analysis, image segmentation, image sequences, learning (artificial intelligence), object detection, spatiotemporal grouping BibRef

Yang, Y.C.[Yan-Chao], Loquercio, A.[Antonio], Scaramuzza, D.[Davide], Soatto, S.[Stefano],
Unsupervised Moving Object Detection via Contextual Information Separation,
CVPR19(879-888).
IEEE DOI 2002
BibRef

Roshan, A., Zhang, Y.,
Moving Object Detection Using Spatial Correlation in LAB Colour Space,
PTVSBB19(173-177).
DOI Link 1912
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Andriyanov, N.A., Vasil'ev, K.K., Dement'ev, V.E.,
Investigation of Filtering and Objects Detection Algorithms for A Multizone Image Sequence,
PTVSBB19(7-10).
DOI Link 1912
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Taran, O., Rezaeifar, S., Holotyak, T., Voloshynovskiy, S.,
Robustification of Deep Net Classifiers by Key Based Diversified Aggregation with Pre-Filtering,
ICIP19(2294-2298)
IEEE DOI 1910
Adversarial attacks, black / gray-box, non-gradient / gradient based attacks, defense, machine learning BibRef

Duque-Arias, D., Velasco-Forero, S., Deschaud, J.E., Goulette, F., Marcotegui, B.,
A Graph-Based Color Lines Model for Image Analysis,
CIAP19(II:181-191).
Springer DOI 1909
Video, initial color lines. BibRef

Xie, R.J.[Ren-Jie], Wang, Y.C.[Yuan-Cheng], Xie, T.[Tian], Zhang, Y.H.[Yu-Hao], Xu, L.[Li], Lu, J.[Jian], Wang, Q.[Qiao],
Adversarial Training for Video Disentangled Representation,
MMMod19(II:532-543).
Springer DOI 1901
Stationary scene and moving objects. BibRef

Shi, H., Liu, C.,
A New Foreground Segmentation Method for Video Analysis in Different Color Spaces,
ICPR18(2899-2904)
IEEE DOI 1812
Image color analysis, Density functional theory, Color, Image segmentation, Probability density function, Motion segmentation BibRef

Ujiie, T., Hiromoto, M., Sato, T.,
Interpolation-Based Object Detection Using Motion Vectors for Embedded Real-time Tracking Systems,
ECVW18(729-7298)
IEEE DOI 1812
Streaming media, Interpolation, Object detection, Detectors, Motion compensation, Real-time systems, Tracking BibRef

Jin, S.[Sou_Young], Roy Chowdhury, A.[Aruni], Jiang, H.[Huaizu], Singh, A.[Ashish], Prasad, A.[Aditya], Chakraborty, D.[Deep], Learned-Miller, E.G.[Erik G.],
Unsupervised Hard Example Mining from Videos for Improved Object Detection,
ECCV18(XIII: 316-333).
Springer DOI 1810
BibRef

Lee, S.H., Jang, W.D., Kim, C.S.,
Temporal Superpixels Based on Proximity-Weighted Patch Matching,
ICCV17(3630-3638)
IEEE DOI 1802
feature extraction, image colour analysis, image matching, image segmentation, motion estimation, PPM motion vectors, Robustness BibRef

Sagawa, R., Satoh, Y.,
Illuminant-Camera Communication to Observe Moving Objects under Strong External Light by Spread Spectrum Modulation,
CVPR17(2317-2325)
IEEE DOI 1711
Cameras, Light sources, Lighting, Modulation, Multiplexing, Signal to noise ratio, Spread, spectrum, communication BibRef

Jain, S.D., Xiong, B., Grauman, K.,
FusionSeg: Learning to Combine Motion and Appearance for Fully Automatic Segmentation of Generic Objects in Videos,
CVPR17(2117-2126)
IEEE DOI 1711
Image segmentation, Motion segmentation, Object segmentation, Optical imaging, Training, Videos BibRef

Yang, R., Ni, B., Ma, C., Xu, Y., Yang, X.,
Video Segmentation via Multiple Granularity Analysis,
CVPR17(6383-6392)
IEEE DOI 1711
Feature extraction, Image segmentation, Noise measurement, Target tracking, Visualization BibRef

Wang, Q.Q.[Qian-Qian], Zhou, X.W.[Xiao-Wei], Hariharan, B.[Bharath], Snavely, N.[Noah],
Learning Feature Descriptors Using Camera Pose Supervision,
ECCV20(I:757-774).
Springer DOI 2011
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Pathak, D., Girshick, R., Dollár, P.[Piotr], Darrell, T.J., Hariharan, B.[Bharath],
Learning Features by Watching Objects Move,
CVPR17(6024-6033)
IEEE DOI 1711
Image segmentation, Motion segmentation, Object detection, Training, Unsupervised learning, Videos BibRef

Zhang, Y.C.[Yu-Chi], Li, G.L.[Guo-Lin], Xie, X.[Xiang], Wang, Z.H.[Zhi-Hua],
A new algorithm for fast and accurate moving object detection based on motion segmentation by clustering,
MVA17(444-447)
DOI Link 1708
Clustering algorithms, Clustering methods, Histograms, Image motion analysis, Motion segmentation, Optical, imaging BibRef

Khodabandeh, M.[Mehran], Muralidharan, S.[Srikanth], Vahdat, A.[Arash], Mehrasa, N.[Nazanin], Pereira, E.M.[Eduardo M.], Satoh, S.[Shin'ichi], Mori, G.[Greg],
Unsupervised learning of supervoxel embeddings for video Segmentation,
ICPR16(2392-2397)
IEEE DOI 1705
Benchmark testing, Context, Feature extraction, Motion segmentation, Partitioning algorithms, Standards, Unsupervised, learning BibRef

Miguel, A., Beery, S., Flores, E., Klemesrud, L., Bayrakcismith, R.,
Finding areas of motion in camera trap images,
ICIP16(1334-1338)
IEEE DOI 1610
Animals BibRef

Gu, S., Wang, J., Pan, L., Cheng, S., Ma, Z., Xie, M.,
Figure/ground video segmentation via low-rank sparse learning,
ICIP16(864-868)
IEEE DOI 1610
Coherence BibRef

Jin, X.[Xin], Guo, K.[Kui], Song, C.G.[Cheng-Gen], Li, X.D.[Xiao-Dong], Zhao, G.[Geng], Luo, J.[Jing], Li, Y.Z.[Yu-Zhen], Chen, Y.Y.[Ying-Ya], Liu, Y.[Yan], Wang, H.C.[Huai-Chao],
Private Video Foreground Extraction Through Chaotic Mapping Based Encryption in the Cloud,
MMMod16(I: 562-573).
Springer DOI 1601
BibRef

Karthikeyan, S., Ngo, T.[Thuyen], Eckstein, M.[Miguel], Manjunath, B.S.,
Eye tracking assisted extraction of attentionally important objects from videos,
CVPR15(3241-3250)
IEEE DOI 1510
BibRef

Kuznetsova, A.[Alina], Hwang, S.J.[Sung Ju], Rosenhahn, B.[Bodo], Sigal, L.[Leonid],
Expanding object detector's Horizon: Incremental learning framework for object detection in videos,
CVPR15(28-36)
IEEE DOI 1510
BibRef

Choy, C.B.[Christopher Bongsoo], Stark, M.[Michael], Corbett-Davies, S.[Sam], Savarese, S.[Silvio],
Enriching object detection with 2D-3D registration and continuous viewpoint estimation,
CVPR15(2512-2520)
IEEE DOI 1510
BibRef

Liu, H.Y.[Hong-Ye], Zhao, T.[Taiyin], Wang, Y.[Yaowei], Tian, Y.H.[Yong-Hong],
A refined object detection method based on HTM,
VCIP14(93-96)
IEEE DOI 1504
image motion analysis BibRef

Perera, S.[Samunda], Barnes, N.M.[Nick M.], He, X.M.[Xu-Ming], Izadi, S.[Shahram], Kohli, P.[Pushmeet], Glocker, B.[Ben],
Motion Segmentation of Truncated Signed Distance Function Based Volumetric Surfaces,
WACV15(1046-1053)
IEEE DOI 1503
Cameras. Truncated signed distance function surface reconstructions. BibRef

Yan, J.Z.[Ji-Zhou], Chen, D.D.[Dong-Dong], Myeong, H.[Heesoo], Shiratori, T.[Takaaki], Ma, Y.[Yi],
Automatic Extraction of Moving Objects from Image and LIDAR Sequences,
3DV14(673-680)
IEEE DOI 1503
Image color analysis BibRef

Rengarajan, V.[Vijay], Rajagopalan, A.N., Aravind, R.,
Motion Estimation and Classification in Compressive Sensing from Dynamic Measurements,
ICPR14(3475-3480)
IEEE DOI 1412
Cameras BibRef

Khoreva, A.[Anna], Galasso, F.[Fabio], Hein, M.[Matthias], Schiele, B.[Bernt],
Classifier based graph construction for video segmentation,
CVPR15(951-960)
IEEE DOI 1510
BibRef
Earlier:
Learning Must-Link Constraints for Video Segmentation Based on Spectral Clustering,
GCPR14(701-712).
Springer DOI 1411
BibRef

Vishnyakov, B.V., Sidyakin, S.V., Vizilter, Y.V.,
Diffusion Background Model for Moving Objects Detection,
PTVSBB15(65-71).
DOI Link 1508
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Vishnyakov, B.V., Gorbatsevich, V., Sidyakin, S.V., Vizilter, Y.V., Malin, I., Egorov, A.,
Fast Moving Objects Detection Using iLBP Background Model,
PCV14(347-350).
DOI Link 1404
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Vishnyakov, B.V., Egorov, A., Sidyakin, S.V., Malin, I., Vizilter, Y.V.,
Statistical Model For Pseudo-Moving Objects Recognition In Video Surveillance Systems,
PCV14(351-356).
DOI Link 1404
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Xu, Y.L.[Yi-Liang], Song, D.Z.[De-Zhen], Hoogs, A.[Anthony],
An Efficient Online Hierarchical Supervoxel Segmentation Algorithm for Time-critical Applications,
BMVC14(xx-yy).
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Faktor, A.[Alon], Irani, M.[Michal],
Video Segmentation by Non-Local Consensus voting,
BMVC14(xx-yy).
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Wang, R.[Rui], Bunyak, F.[Filiz], Seetharaman, G.[Guna], Palaniappan, K.[Kannappan],
Static and Moving Object Detection Using Flux Tensor with Split Gaussian Models,
CDW14(420-424)
IEEE DOI 1409
Gaussian model BibRef

Weinzaepfel, P.[Philippe], Revaud, J.[Jerome], Harchaoui, Z.[Zaid], Schmid, C.[Cordelia],
Learning to detect Motion Boundaries,
CVPR15(2578-2586)
IEEE DOI 1510
BibRef

Elqursh, A.[Ali], Elgammal, A.M.[Ahmed M.],
Online Motion Segmentation Using Dynamic Label Propagation,
ICCV13(2008-2015)
IEEE DOI 1403
BibRef

Neubert, P.[Peer], Schubert, S.[Stefan],
Hyperdimensional computing as a framework for systematic aggregation of image descriptors,
CVPR21(16933-16942)
IEEE DOI 2111
Systematics, Aggregates, Semantics, Memory management, Layout, Tools BibRef

Neubert, P.[Peer], Protzel, P.[Peter],
Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation,
BMVC13(xx-yy).
DOI Link 1402
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Couprie, C.[Camille], Farabet, C.[Clement], Le Cun, Y.L.[Yann L.], Najman, L.[Laurent],
Causal graph-based video segmentation,
ICIP13(4249-4253)
IEEE DOI 1402
Optimization, graph-matching, superpixels BibRef

Feng, W.G.[Wei-Guo], Liu, R.[Rui], Jia, B.Z.[Bao-Zhi], Zhu, M.[Ming],
An efficient pixel-wise method for moving object detection in complex scenes,
AVSS13(389-394)
IEEE DOI 1311
Adaptation models BibRef

Allekotte, K.[Kevin], de Cristóforis, P.[Pablo], Melita, M.[Mario], Mejail, M.[Marta],
Astronomical Image Data Reduction for Moving Object Detection,
CIARP13(II:116-123).
Springer DOI 1311
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Walha, A.[Ahlem], Wali, A.[Ali], Alimi, A.M.[Adel M.],
Moving Object Detection System in Aerial Video Surveillance,
ACIVS13(310-320).
Springer DOI 1311
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Tang, K.[Kevin], Sukthankar, R.[Rahul], Yagnik, J.[Jay], Fei-Fei, L.[Li],
Discriminative Segment Annotation in Weakly Labeled Video,
CVPR13(2483-2490)
IEEE DOI 1309
Learning from internet videos. Tags may not be right. Focus here on segmentation. BibRef

Flores-Mangas, F.[Fernando], Jepson, A.D.[Allan D.],
Fast Rigid Motion Segmentation via Incrementally-Complex Local Models,
CVPR13(2259-2266)
IEEE DOI 1309
Model Selection BibRef

Shin, Y.D.[Yong-Deuk], Park, J.H.[Jae-Han], Jang, G.R.[Ga-Ram], Baeg, M.H.[Moon-Hong],
Moving objects detection using freely moving depth sensing camera,
ICPR12(1314-1317).
WWW Link. 1302
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Ji, H.[Hao], Su, F.[Fei],
Robust motion segmentation via refined sparse subspace clustering,
ICPR12(1546-1549).
WWW Link. 1302
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Zhang, S.H.[Shang-Hang], Wei, K.J.[Kai-Jin], Jia, H.Z.[Hui-Zhu], Xie, X.D.[Xiao-Dong], Gao, W.[Wen],
An efficient foreground-based surveillance video coding scheme in low bit-rate compression,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Luo, Z.Y.[Zheng-Yi], Song, L.[Li], Zheng, S.B.[Shi-Bao], Ling, N.[Nam],
Optimized nested protection for video Region of Interest with Raptor codes,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Wang, F.P.[Fu-Ping], Chung, W.H.[Wei-Ho], Ni, G.K.[Guo-Kai], Chen, I.Y.[Ing-Yi], Kuo, S.Y.[Sy-Yen],
Moving Object Extraction Using Compressed Domain Features of H.264 INTRA Frames,
AVSS12(258-263).
IEEE DOI 1211
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Izadinia, H., Saleemi, I.[Imran], Shah, M.[Mubarak],
Multimodal Analysis for Identification and Segmentation of Moving-Sounding Objects,
MultMed(15), No. 2, 2013, pp. 378-390.
IEEE DOI 1302
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Dey, S.[Soumyabrata], Reilly, V.[Vladimir], Saleemi, I.[Imran], Shah, M.[Mubarak],
Detection of Independently Moving Objects in Non-planar Scenes via Multi-Frame Monocular Epipolar Constraint,
ECCV12(V: 860-873).
Springer DOI 1210
Video:
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Lee, J.H.[Ju-Ho], Kwak, S.[Suha], Han, B.H.[Bo-Hyung], Choi, S.J.[Seung-Jin],
Online Video Segmentation by Bayesian Split-Merge Clustering,
ECCV12(IV: 856-869).
Springer DOI 1210
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Paiton, D.M., Brumby, S.P., Kenyon, G.T., Kunde, G.J., Peterson, K.D., Ham, M.I., Schultz, P.F., George, J.S.,
Combining multiple visual processing streams for locating and classifying objects in video,
Southwest12(49-52).
IEEE DOI 1205
On large dataset of aerial video. BibRef

Papon, J.[Jeremie], Abramov, A.[Alexey], Wörgötter, F.[Florentin],
Occlusion Handling in Video Segmentation via Predictive Feedback,
ARTEMIS12(III: 233-242).
Springer DOI 1210

See also Real-Time Segmentation of Stereo Videos on a Portable System With a Mobile GPU. BibRef

Wang, Y.Y.[Yi-Ying], Lee, C.H.[Chia-Han],
Segmentation by temporal detection integration,
ICIP11(3125-3128).
IEEE DOI 1201
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Mondal, A.[Ajoy], Ghosh, S.[Susmita], Ghosh, A.[Ashish],
Distributed differential evolution algorithm for MAP estimation of MRF model for detecting moving objects,
ICIIP11(1-6).
IEEE DOI 1112
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Ding, J.W.[Jian-Wei], Li, M.[Min], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Modeling Complex Scenes for Accurate Moving Objects Segmentation,
ACCV10(II: 82-94).
Springer DOI 1011
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Chen, A.Y.C.[Albert Y. C.], Corso, J.J.[Jason J.],
Temporally consistent multi-class video-object segmentation with the Video Graph-Shifts algorithm,
WMVC11(614-621).
IEEE DOI 1101
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Zografos, V.[Vasileios],
Enhancing motion segmentation by combination of complementary affinities,
ICPR12(2198-2201).
WWW Link. 1302
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Zografos, V.[Vasileios], Nordberg, K.[Klas],
Fast and accurate motion segmentation using Linear Combination of Views,
BMVC11(xx-yy).
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Zografos, V.[Vasileios], Nordberg, K.[Klas], Ellis, L.[Liam],
Sparse Motion Segmentation Using Multiple Six-Point Consistencies,
VECTaR10(338-348).
Springer DOI 1109
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Nordberg, K.[Klas], Zografos, V.[Vasileios],
Multibody Motion Segmentation Using the Geometry of 6 Points in 2D Images,
ICPR10(1783-1787).
IEEE DOI 1008
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Boukharouba, K.[Khaled], Bako, L.[Laurent], Lecoeuche, S.[Stephane],
Temporal video segmentation using a switched affine models identification technique,
IPTA10(157-160).
IEEE DOI 1007
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van Essen, G., Marsland, S., Lewis, J.,
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IVCNZ09(425-430).
IEEE DOI 0911
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Wang, Y.J.[Yan-Jiang], Suo, P.[Peng], Qi, Y.J.[Yu-Juan],
Memorizing GMM to Handle Sharp Changes in Moving Object Segmentation,
CISP09(1-4).
IEEE DOI 0910
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Zhang, Y.[Yan], Chen, K.[Kai], Wang, H.J.[Hui-Jing], Zhou, Y.[Yi], Guan, H.B.[Hai-Bing],
Two-View Motion Segmentation by Gaussian Blurring Mean Shift with Fitness Measure,
CISP09(1-6).
IEEE DOI 0910
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Wang, Y.N.[Yan-Ni], Fan, Y.Y.[Yang-Yu],
Adaptive Motion Segmentation Based on Genetic Algorithm,
CISP09(1-4).
IEEE DOI 0910
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Girisha, R., Murali, S.,
Segmentation of motion objects from surveillance video sequences using partial correlation,
ICIP09(1129-1132).
IEEE DOI 0911
BibRef
Earlier: A2, A1:
Segmentation of Motion Objects from Surveillance Video Sequences Using Temporal Differencing Combined with Multiple Correlation,
AVSBS09(472-477).
IEEE DOI 0909
BibRef

Liu, F.[Feng], Gleicher, M.[Michael],
Learning color and locality cues for moving object detection and segmentation,
CVPR09(320-327).
IEEE DOI 0906
BibRef

Baradarani, A.[Aryaz], Wu, J.[Jonathan],
Moving object segmentation using the 9/7-10/8 dual-tree complex filter bank,
ICPR08(1-4).
IEEE DOI 0812
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Fraile, R.[Roberto], Hogg, D.C.[David C.], Cohn, A.G.[Anthony G.],
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ICPR08(1-4).
IEEE DOI 0812
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Li, H.W.[Hong-Wei], Lin, L.[Liang], Wu, T.F.[Tian-Fu], Liu, X.B.[Xiao-Bai], Dong, L.F.[Lan-Fang],
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ICPR08(1-4).
IEEE DOI 0812
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Zhang, T.Z.[Tian-Zhu], Li, S.Z.[Stan Z.], Xiang, S.M.[Shi-Ming], Zhang, L.[Lun], Liu, S.[Si],
Co-Training Based Segmentation of Merged Moving Objects,
VS08(xx-yy). 0810
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Brostow, G.J.[Gabriel J.], Shotton, J.D.J.[Jamie D.J.], Fauqueur, J.[Julien], Cipolla, R.[Roberto],
Segmentation and Recognition Using Structure from Motion Point Clouds,
ECCV08(I: 44-57).
Springer DOI 0810
Might be more a depth segmentation paper. Object segmentation using motion derived 3D data. BibRef

Fradet, M.[Matthieu], Pérez, P.[Patrick], Robert, P.[Philippe],
Semi-automatic Motion Segmentation with Motion Layer Mosaics,
ECCV08(III: 210-223).
Springer DOI 0810
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Langs, G.[Georg], Paragios, N.[Nikos],
Modeling the structure of multivariate manifolds: Shape maps,
CVPR08(1-8).
IEEE DOI 0806
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Yoo, Y.S.[Yong-Seok], Park, T.S.[Tae-Suh],
A moving object detection algorithm for smart cameras,
EmbedCV08(1-8).
IEEE DOI 0806
BibRef

Monteiro, F.C.[Fernando C.], Campilho, A.[Aurélio],
Region and Graph-Based Motion Segmentation,
ICIAR08(xx-yy).
Springer DOI 0806
BibRef

Venetianer, P.L., Zhang, Z., Yin, W., Lipton, A.J.,
Stationary target detection using the ObjectVideo surveillance system,
AVSBS07(242-247).
IEEE DOI 0709

See also ObjectVideo. BibRef

Wei, Z.Y.[Zhao-Yi], Lee, D.J.[Dah-Jye], Jilk, D.[David], Schoenberger, R.[Robert],
Motion Projection for Floating Object Detection,
ISVC07(II: 152-161).
Springer DOI 0711
BibRef

Toussaint, M., Willert, V.[Volker], Eggert, J.[Julian], Korner, E.,
Motion Segmentation Using Inference in Dynamic Bayesian Networks,
BMVC07(xx-yy).
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Hu, H.[Han], Gu, Q.Q.[Quan-Quan], Deng, L.[Lei], Zhou, J.[Jie],
Multiframe Motion Segmentation via Penalized Map Estimation and Linear Programming,
BMVC09(xx-yy).
PDF File. 0909
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Verbeke, N.[Nicolas], Vincent, N.[Nicole],
A PCA-Based Technique to Detect Moving Objects,
SCIA07(641-650).
Springer DOI 0706
BibRef

Lee, D.G.[Dong-Gyu], Han, S.Y.[Su-Young],
Shape Preserving Hierarchical Triangular Mesh for Motion Estimation,
PSIVT06(929-938).
Springer DOI 0612
Motion detection, change the mesh. BibRef

Park, S.Y.[Soon-Yong], Moon, J.Y.[Jaek-Young], Park, C.J.[Chang-Joon], Lee, I.H.[In-Ho],
Moving Object Removal Based on Global Feature Registration,
ACIVS06(275-286).
Springer DOI 0609
BibRef

Dupont, R.[Romain], Juan, O.[Olivier], Keriven, R.[Renaud],
Robust Segmentation of Hidden Layers in Video Sequences,
ICPR06(III: 75-78).
IEEE DOI 0609
BibRef

Yamazaki, M.[Masaki], Xu, G.[Gang], Chen, Y.W.[Yen-Wei],
Detection of Moving Objects by Independent Component Analysis,
ACCV06(II:467-478).
Springer DOI 0601

See also Separating Reflections from Images Using Kernel Independent Component Analysis. BibRef

Wang, J.[Jia], Wang, H.F.[Hai-Feng], Liu, Q.S.[Qing-Shan], Lu, H.Q.[Han-Qing],
Automatic Moving Object Segmentation with Accurate Boundaries,
ACCV06(I:276-285).
Springer DOI 0601
BibRef

Liu, Y.Z.[Ya-Zhou], Gao, W.[Wen], Yao, H.X.[Hong-Xun], Liu, S.H.[Shao-Hui], Wang, L.J.[Li-Jun],
Fast Moving Region Detection Scheme in Ad Hoc Sensor Network,
ICIAR04(II: 520-527).
Springer DOI 0409
BibRef

Carminati, L., Benois-Pineau, J.,
Gaussian Mixture Classification for Moving Object Detection in Video Surveillance Environment,
ICIP05(III: 113-116).
IEEE DOI 0512
BibRef

Dupont, R.[Romain], Paragios, N.[Nikos], Keriven, R.[Renaud], Fuchs, P.[Phillipe],
Extraction of Layers of Similar Motion Through Combinatorial Techniques,
EMMCVPR05(220-234).
Springer DOI 0601
BibRef

Solomon, J., Butman, J.A., Sood, A.,
Segmentation of Objects in Temporal Images Using the Hidden Markov Model,
ICIP05(I: 1-4).
IEEE DOI 0512
BibRef

Wang, Y.[Yang], Ji, Q.A.[Qi-Ang],
A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences,
CVPR05(I: 264-270).
IEEE DOI 0507
BibRef

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Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Video Object Segmentation .