20.4.4.10.4 Object Extraction, Object Detection for Database Indexing

Chapter Contents (Back)
Database. Image Database. Background. Foreground. Salient Regions.

Li, W.S., Candan, K.S., Hirata, K., Hara, Y.,
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Li, W.S.[Wen-Syan], Candan, K.S.[Kasim S.],
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Stricker, M., Dimai, A.,
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MVA(10), No. 2, 1997, pp. 66-73.
Springer DOI 9707
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Earlier:
Color indexing with weak spatial constraints,
SPIE1996, Storage Retrieval Still Image Video Databases IV, pp. 29-40. Based on extracted salient regions. BibRef

Dimai, A.,
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CIAP99(957-962).
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Dimai, A.,
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CIAP99(686-691).
IEEE DOI 9909
Find salient regions. BibRef

Pauwels, E.J., Frederix, G.,
Finding Salient Regions in Images,
CVIU(75), No. 1/2, July-August 1999, pp. 73-85.
DOI Link Map into nonparametric space. Isolation and Connectivity used to merge regions. BibRef 9907

Pauwels, E.J., Frederix, G., Caenen, G.,
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ICIP01(III: 66-69).
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Pauwels, E.J., Frederix, G.,
Image Segmentation by Nonparametric Clustering based on the Kolmogorov-Smirnov Distance,
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Pauwels, E.J., Frederix, G.,
Cluster-based Segmentation of Natural Scenes,
ICCV99(997-1002).
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Frederix, G., Caenen, G., Pauwels, E.J.,
Pariss: Panoramic, Adaptive and Reconfigurable Interface for Similarity Search,
ICIP00(Vol III: 222-225).
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Luo, J.B.[Jie-Bo], Etz, S.P.,
A physical model-based approach to detecting sky in photographic images,
IP(11), No. 3, March 2002, pp. 201-212.
IEEE DOI 0203
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And:
A physics-motivated approach to detecting sky in photographs,
ICPR02(I: 155-158).
IEEE DOI 0211
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Gallagher, A.C., Luo, J.B.[Jie-Bo], Hao, W.[Wei],
Improved blue sky detection using polynomial model fit,
ICIP04(IV: 2367-2370).
IEEE DOI 0505
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Yoo, H.W.[Hun-Woo], Jung, S.H.[She-Hwan], Jang, D.S.[Dong-Sik], Na, Y.K.[Yoon-Kyoon],
Extraction of major object features using VQ clustering for content-based image retrieval,
PR(35), No. 5, May 2002, pp. 1115-1126.
Elsevier DOI 0202
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Lau, H.F.[Hang Fai], Levine, M.D.[Martin D.],
Finding a small number of regions in an image using low-level features,
PR(35), No. 11, November 2002, pp. 2323-2339.
Elsevier DOI 0208
Low level processing to aid in finding important objects for image retrieval, etc. Simple threshold measure gave better results than more complex measures tested (
See also Finding Salient Regions in Images. ) and Modified Hubert Index. BibRef

Sun, S.J.[Shi-Jun], Haynor, D.R., Kim, Y.M.[Yong-Min],
Semiautomatic video object segmentation using vsnakes,
CirSysVideo(13), No. 1, January 2003, pp. 75-82.
IEEE Top Reference. 0301
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Hsieh, J.W.[Jun-Wei], Grimson, W.E.L.,
Spatial template extraction for image retrieval by region matching,
IP(12), No. 11, November 2003, pp. 1404-1415.
IEEE DOI 0311
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Hsieh, J.W.,
Region-based Image Retrieval,
ICIP00(Vol I: 77-80).
IEEE DOI 0008
BibRef

Kim, J.S.[Jin-Sang], Chen, T.,
A VLSI architecture for video-object segmentation,
CirSysVideo(13), No. 1, January 2003, pp. 83-96.
IEEE Top Reference. 0301
BibRef

van Assen, H.C., Egmont-Petersen, M., Reiber, J.H.C.,
Accurate object localization in gray level images using the center of gravity measure: accuracy versus precision,
IP(11), No. 12, December 2002, pp. 1379-1384.
IEEE DOI 0301
BibRef

Kim, J., Chen, T.,
Combining static and dynamic features using neural networks and edge fusion for video object extraction,
VISP(150), No. 3, June 2003, pp. 160-167.
IEEE Abstract. 0308
BibRef

Luo, J.B.[Jie-Bo], Singhal, A.[Amit], Etz, S.P.[Stephen P.], Gray, R.T.[Robert T.],
A computational approach to determination of main subject regions in photographic images,
IVC(22), No. 3, 1 March 2004, pp. 227-241.
Elsevier DOI 0402
Find the salient region. BibRef

Sun, Z.H.[Ze-Hang], Bebis, G.N.[George N.], Miller, R.[Ronald],
Object detection using feature subset selection,
PR(37), No. 11, November 2004, pp. 2165-2176.
Elsevier DOI 0409
BibRef
Earlier:
Boosting object detection using feature selection,
AVSBS03(290-296).
IEEE DOI 0310
BibRef

Li, L., Huang, W., Gu, I.Y.H., Tian, Q.,
Statistical Modeling of Complex Backgrounds for Foreground Object Detection,
IP(13), No. 11, November 2004, pp. 1459-1472.
IEEE DOI 0411
BibRef

Liu, Z.[Zhi], Yang, J.[Jie], Peng, N.S.[Ning Song],
Semi-automatic video object segmentation using seeded region merging and bidirectional projection,
PRL(26), No. 5, April 2005, pp. 653-662.
Elsevier DOI 0501
BibRef

Peng, N.S.[Ning Song], Yang, J.[Jie], Liu, Z.[Zhi],
Mean shift blob tracking with kernel histogram filtering and hypothesis testing,
PRL(26), No. 5, April 2005, pp. 605-614.
Elsevier DOI 0501
BibRef
Earlier: A1, A2, Only:
Mean-Shift Blob Tracking with Kernel-Color Distribution Estimate and Adaptive Model Update Criterion,
SMVP04(83-93).
Springer DOI 0505
BibRef

Pu, J.X.[Jie-Xin], Peng, N.S.[Ning-Song],
Adaptive Kernel Based Tracking Using Mean-Shift,
ICIAR06(I: 394-403).
Springer DOI 0610
BibRef

Ahmad, A.M.A.[Ashraf M.A.], Lee, S.Y.[Suh-Yin],
Robust Compressed Domain Object Extraction in MPEG Videos,
GVIP(05), No. V7, 2005, pp. xx-yy
HTML Version. BibRef 0500

Amores, J., Radeva, P.I.,
Registration and retrieval of highly elastic bodies using contextual information,
PRL(26), No. 11, August 2005, pp. 1720-1731.
Elsevier DOI 0506
BibRef

Amores, J.[Jaume], Sebe, N.[Nicu], Radeva, P.I.[Petia I.],
Context-Based Object-Class Recognition and Retrieval by Generalized Correlograms,
PAMI(29), No. 10, October 2007, pp. 1818-1833.
IEEE DOI 0710
BibRef
And:
Class-Specific Binary Correlograms for Object Recognition,
BMVC07(xx-yy).
PDF File. 0709
Generalized Correlograms to retrieve object categories.
See also Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier. BibRef

Cao, F.[Frédéric], Musé, P.[Pablo], Sur, F.[Frédéric],
Extracting Meaningful Curves from Images,
JMIV(22), No. 2-3, May 2005, pp. 159-181.
Springer DOI 0505
BibRef
Earlier: INRIARR-5067, 2003.
HTML Version.
See also A Contrario Decision Method for Shape Element Recognition, An. BibRef

Muse, P., Sur, F., Cao, F., Gousseau, Y.[Yann],
Unsupervised thresholds for shape matching,
ICIP03(II: 647-650).
IEEE DOI 0312
Shape queries BibRef

He, Z.,
Dynamic programming framework for automatic video object segmentation and vision-assisted video pre-processing,
VISP(152), No. 5, October 2005, pp. 597-603.
DOI Link 0512
BibRef

Han, J., Ngan, K.N., Li, M., Zhang, H.J.,
Unsupervised Extraction of Visual Attention Objects in Color Images,
CirSysVideo(16), No. 1, January 2006, pp. 141-145.
IEEE DOI 0601
BibRef

Luo, J.B.[Jie-Bo], Crandall, D.,
Color Object Detection Using Spatial-Color Joint Probability Functions,
IP(15), No. 6, June 2006, pp. 1443-1453.
IEEE DOI 0606
BibRef
Earlier: A2, A1:
Robust color object detection using spatial-color joint probability functions,
CVPR04(I: 379-385).
IEEE DOI 0408
Color edge co-occurence histogram. Find specific color images (patterns) in an image. BibRef

Zhang, H.M.[Hong-Ming], Gao, W.[Wen], Chen, X.L.[Xi-Lin], Zhao, D.B.[De-Bin],
Object detection using spatial histogram features,
IVC(24), No. 4, 1 April 2006, pp. 327-341.
Elsevier DOI 0606
Spatial histogram features; Feature selection; Histogram matching; Support vector machine Distributions over patches, preserve shape and texture. BibRef

Bergboer, N.H.[Niek H.], Postma, E.O.[Eric O.], van den Herik, H.J.[H. Jaap],
Context-based object detection in still images,
IVC(24), No. 9, September 2006, pp. 987-1000.
Elsevier DOI 0608
Machine learning; Object recognition Two stages, first find objects, then assign confidence based on context. BibRef

Bergboer, N.H.[Niek H.], Postma, E.O.[Eric O.], van den Herik, H.J.[H. Jaap],
Accuracy versus speed in context-based object detection,
PRL(28), No. 6, 15 April 2007, pp. 686-694.
Elsevier DOI 0703
Object detection; Face detection; Machine learning BibRef

Lu, H.H.[Hui-Hai], Woods, J.C.[John C.], Ghanbari, M.[Mohammed],
Binary Partition Tree for Semantic Object Extraction and Image Segmentation,
CirSysVideo(17), No. 3, March 2007, pp. 378-383.
IEEE DOI 0703
BibRef

Lu, H.H.[Hui-Hai], Woods, J.C.[John C.], Ghanbari, M.[Mohammed],
Binary Partition Tree Analysis Based on Region Evolution and Its Application to Tree Simplification,
IP(16), No. 4, April 2007, pp. 1131-1138.
IEEE DOI 0704
BibRef

Chevalier, F., Domenger, J.P., Benois-Pineau, J., Delest, M.,
Retrieval of objects in video by similarity based on graph matching,
PRL(28), No. 8, 1 June 2007, pp. 939-949.
Elsevier DOI 0704
Video object matching; Rough indexing paradigm; Relaxation; Inexact graph matching; CBIR BibRef

Morand, C., Benois-Pineau, J., Domenger, J.P., Zepeda, J., Kijak, E., Guillemot, C.,
Scalable Object-Based Video Retrieval in HD Video Databases,
SP:IC(25), No. 6, July 2010, pp. 450-465.
Elsevier DOI 1007
HD video; Scalable video object extraction; Object-based indexing; Video retrieval BibRef

Chevalier, F.[Fanny], Delest, M.[Maylis], Domenger, J.P.[Jean-Philippe],
A heuristic for the retrieval of objects in video in the framework of the rough indexing paradigm,
SP:IC(22), No. 7-8, August-September 2007, pp. 622-634.
Elsevier DOI 0710
Video object retrieval; Rough indexing paradigm; Error-tolerant graph matching; Heuristic BibRef

Wang, J.B.[Jing-Bin], Athitsos, V.[Vassilis], Sclaroff, S.[Stan], Betke, M.[Margrit],
Detecting Objects of Variable Shape Structure With Hidden State Shape Models,
PAMI(30), No. 3, March 2008, pp. 477-492.
IEEE DOI 0801
BibRef
Earlier: A2, A1, A3, A4:
Detecting Instances of Shape Classes That Exhibit Variable Structure,
ECCV06(I: 121-134).
Springer DOI 0608
BibRef

Wu, Z.[Zheng], Betke, M.[Margrit], Wang, J.B.[Jing-Bin], Athitsos, V.[Vassilis], Sclaroff, S.[Stan],
Tracking with Dynamic Hidden-State Shape Models,
ECCV08(I: 643-656).
Springer DOI 0810
BibRef

Wang, J.B.[Jing-Bin], Gu, E.[Erdan], Betke, M.[Margrit],
MosaicShape: Stochastic Region Grouping with Shape Prior,
CVPR05(I: 902-908).
IEEE DOI 0507
Combine shape based recognition and image segmentation. BibRef

Lu, Y.[Ye], Li, Z.N.[Ze-Nian],
Automatic object extraction and reconstruction in active video,
PR(41), No. 3, March 2008, pp. 1159-1172.
Elsevier DOI 0711
BibRef
Earlier:
Object Extraction and Reconstruction in Active Video,
CRV06(73-73).
IEEE DOI 0607
Active video; Camera motions; Shift and hold; Object extraction; 3D object reconstruction BibRef

Liu, Y.[Yi], Zheng, Y.F.[Yuan F.], Shen, X.T.[Xiao-Tong],
Applying the multi-category learning to multiple video object extraction,
PR(41), No. 9, September 2008, pp. 2777-2788.
Elsevier DOI 0806
VO extraction; Multiple object tracking; [psi]-Learning; Support vector machines (SVM); Multi-class classification BibRef

Jan, Y.H.[Yih-Haw], Lin, D.W.[David W.],
Edge-Based Morphological Processing for Efficient and Accurate Video Object Extraction,
IEICE(E88-D), No. 2, February 2005, pp. 335-340.
DOI Link 0502
BibRef

Watanabe, M.[Mutsumi],
Adaptive Decomposition of Dynamic Scene into Object-Based Distribution Components Based on Mixture Model Framework,
IEICE(E88-D), No. 4, April 2005, pp. 758-766.
DOI Link 0504
BibRef

da Rugna, J.[Jérôme], Konik, H.[Hubert],
A Robust Approach to Segment Desired Object Based on Salient Colors,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
BibRef

Zhu, S., Liu, Y.,
Scene Segmentation and Semantic Representation for High-Level Retrieval,
SPLetters(15), No. 1, 2008, pp. 713-716.
IEEE DOI 0812
BibRef

Liu, D.[David], Chen, T.H.[Tsu-Han],
Video retrieval based on object discovery,
CVIU(113), No. 3, March 2009, pp. 397-404.
Elsevier DOI 0902
BibRef
Earlier:
Object discovery with perceptual grouping,
ICIP08(3032-3035).
IEEE DOI 0810
BibRef
Earlier:
Unsupervised Image Categorization and Object Localization using Topic Models and Correspondences between Images,
ICCV07(1-7).
IEEE DOI 0710
BibRef
And:
A Topic-Motion Model for Unsupervised Video Object Discovery,
CVPR07(1-8).
IEEE DOI 0706
BibRef
And:
Background Cutout with Automatic Object Discovery,
ICIP07(IV: 345-348).
IEEE DOI 0709
Video retrieval; Video matching; Unsupervised object discovery Motion ambiguities resolved by appearance, appearance ambiguities by motion. BibRef

Liu, D.[David], Chen, T.H.[Tsu-Han],
DISCOV: A Framework for Discovering Objects in Video,
MultMed(10), No. 2, February 2008, pp. 200-208.
IEEE DOI 0905
BibRef
Earlier:
Semantic-Shift for Unsupervised Object Detection,
BP06(16).
IEEE DOI 0609
BibRef

Liu, D.[David], Hua, G.[Gang], Chen, T.H.[Tsu-Han],
A Hierarchical Visual Model for Video Object Summarization,
PAMI(32), No. 12, December 2010, pp. 2178-2190.
IEEE DOI 1011
BibRef
Earlier:
VideoCut: Removing Irrelevant Frames by Discovering the Object of Interest,
ECCV08(I: 441-453).
Springer DOI 0810
Given a frame labeling for a few frames remove irrelevant frames. BibRef

Liu, D.[David], Chen, D.T.[Da-Tong], Chen, T.H.[Tsu-Han],
Unsupervised Image Layout Extraction,
ICIP06(1113-1116).
IEEE DOI 0610
BibRef
And:
Latent Layout Analysis for Discovering Objects in Images,
ICPR06(II: 468-471).
IEEE DOI 0609
BibRef

Bouveyron, C.[Charles], Girard, S.C.[Stephane C.],
Robust supervised classification with mixture models: Learning from data with uncertain labels,
PR(42), No. 11, November 2009, pp. 2649-2658.
Elsevier DOI 0907
Supervised classification; Data with uncertain labels; Mixture models; Robustness; Label noise; Weakly supervised classification BibRef

Laskar, Z.[Zakaria], Kannala, J.H.[Ju-Ho],
Data-efficient Ranking Distillation for Image Retrieval,
ACCV20(I:469-484).
Springer DOI 2103
BibRef
And:
Context Aware Query Image Representation for Particular Object Retrieval,
SCIA17(II: 88-99).
Springer DOI 1706
BibRef

Bouveyron, C.[Charles], Kannala, J.H., Schmid, C., Girard, S.C.[Stephane C.],
Object Localization by Subspace Clustering of Local Descriptors,
ICCVGIP06(457-467).
Springer DOI 0612
BibRef

Withagen, P.J., Schutte, K., Groen, F.C.A.,
Global Intensity Correction in Dynamic Scenes,
IJCV(86), No. 1, January 2010, pp. xx-yy.
Springer DOI 1001
BibRef
Earlier:
Probabilistic classication between foreground objects and background,
ICPR04(I: 31-34).
IEEE DOI 0409
BibRef
Earlier:
Likelihood-based object detection and object tracking using color histograms and EM,
ICIP02(I: 589-592).
IEEE DOI 0210
BibRef

Millet, C.[Christophe], Bloch, I.[Isabelle], Hede, P.[Patrick], Moellic, P.A.[Pierre-Alain],
Automatic cleaning and segmentation of web images based on colors to build learning databases,
IVC(28), No. 3, March 2010, pp. 317-328.
Elsevier DOI 1001
Semantics; Web images; Automatic segmentation; Sorting images Segment by color and central object, combine. BibRef

Lecca, M.[Michela],
An Attention Module for Object Detection in Cluttered Images,
ELCVIA(8), No. 2, July 2009, pp. xx-yy.
DOI Link 1002
BibRef

Liu, G.C.[Guang-Can], Lin, Z.C.[Zhou-Chen], Tang, X.[Xiaoou], Yu, Y.[Yong],
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM),
PAMI(32), No. 5, May 2010, pp. 910-924.
IEEE DOI 1003
BibRef
Earlier:
A Hybrid Graph Model for Unsupervised Object Segmentation,
ICCV07(1-8).
IEEE DOI 0710
Automatic segmentation without annotated training images. Graph representation of the desired objects.o BibRef

Zhong, P.[Ping], Wang, R.S.[Run-Sheng],
Learning Sparse CRFs for Feature Selection and Classification of Hyperspectral Imagery,
GeoRS(46), No. 12, December 2008, pp. 4186-4197.
IEEE DOI 0812
BibRef

Qian, Z.M.[Zhi-Ming], Zhong, P.[Ping], Wang, R.S.[Run-Sheng],
Personalized image annotation via class-specific cross-domain learning,
SP:IC(34), No. 1, 2015, pp. 61-71.
Elsevier DOI 1505
BibRef
Earlier: A2, A1, A3:
Dynamic Learning of SCRF for Feature Selection and Classification of Hyperspectral Imagery,
SSSPR12(254-263).
Springer DOI 1211
Personalized image annotation BibRef

Qian, Z.M.[Zhi-Ming], Zhong, P.[Ping], Wang, R.S.[Run-Sheng],
Tag Refinement for User-Contributed Images via Graph Learning and Nonnegative Tensor Factorization,
SPLetters(22), No. 9, September 2015, pp. 1302-1305.
IEEE DOI 1503
graph theory BibRef

Zhong, P.[Ping], Wang, R.S.[Run-Sheng],
Learning Conditional Random Fields for Classification of Hyperspectral Images,
IP(19), No. 7, July 2010, pp. 1890-1907.
IEEE DOI 1007
BibRef
Earlier:
Object Detection Based on Combination of Conditional Random Field and Markov Random Field,
ICPR06(III: 160-163).
IEEE DOI 0609

See also Using Combination of Statistical Models and Multilevel Structural Information for Detecting Urban Areas From a Single Gray-Level Image. BibRef

Zhong, P.[Ping], Wang, R.S.[Run-Sheng],
Modeling and Classifying Hyperspectral Imagery by CRFs With Sparse Higher Order Potentials,
GeoRS(49), No. 2, February 2011, pp. 688-705.
IEEE DOI 1102
BibRef

Zhong, P.[Ping], Wang, R.S.[Run-Sheng],
Multiple-Spectral-Band CRFs for Denoising Junk Bands of Hyperspectral Imagery,
GeoRS(51), No. 4, April 2013, pp. 2260-2275.
IEEE DOI 1304
BibRef

Chung, C.H.[Chi-Han], Cheng, S.C.[Shyi-Chyi], Chang, C.C.[Chin-Chun],
Adaptive image segmentation for region-based object retrieval using generalized Hough transform,
PR(43), No. 10, October 2010, pp. 3219-3232.
Elsevier DOI 1007
Object recognition; Hough transform; Image segmentation; Information retrieval BibRef

Fu, H.[Hong], Chi, Z.[Zheru], Feng, D.D.[David Dagan],
Recognition of attentive objects with a concept association network for image annotation,
PR(43), No. 10, October 2010, pp. 3539-3547.
Elsevier DOI 1007
Image annotation; Concept association network (CAN); Attentive objects; Visual classifier; Neural network BibRef

Liu, T.[Tie], Yuan, Z.J.[Ze-Jian], Sun, J.[Jian], Wang, J.D.[Jing-Dong], Zheng, N.N.[Nan-Ning], Tang, X.[Xiaoou], Shum, H.Y.[Heung-Yeung],
Learning to Detect a Salient Object,
PAMI(33), No. 2, February 2011, pp. 353-367.
IEEE DOI 1101
Binary labeling task, separate object from background. Contrast, center-surround histogram, color spatial distribtuion, multi-level description. BibRef

Liu, T.[Tie], Zheng, N.N.[Nan-Ning], Wei, Yuan, Z.J.[Ze-Jian],
Video attention: Learning to detect a salient object sequence,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Liu, T.[Tie], Sun, J.[Jian], Zheng, N.N.[Nan-Ning], Tang, X.[Xiaoou], Shum, H.Y.[Heung-Yeung],
Learning to Detect A Salient Object,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Spain, M.[Merrielle], Perona, P.[Pietro],
Measuring and Predicting Object Importance,
IJCV(91), No. 1, January 2011, pp. 59-76.
WWW Link. 1101
BibRef
Earlier:
Some Objects Are More Equal Than Others: Measuring and Predicting Importance,
ECCV08(I: 523-536).
Springer DOI 0810
Computed from simple region measures, not recognition. BibRef

Lu, Z.W.[Zhi-Wu], Ip, H.H.S.[Horace H.S.], Peng, Y.X.[Yu-Xin],
Contextual Kernel and Spectral Methods for Learning the Semantics of Images,
IP(20), No. 6, June 2011, pp. 1739-1750.
IEEE DOI 1106
To annotate with keywords
See also Spectral learning of latent semantics for action recognition. BibRef

Sidiropoulos, P.[Panagiotis], Mezaris, V., Kompatsiaris, I., Meinedo, H., Bugalho, M., Trancoso, I.,
Temporal Video Segmentation to Scenes Using High-Level Audiovisual Features,
CirSysVideo(21), No. 8, August 2011, pp. 1163-1177.
IEEE DOI 1108
BibRef

Sidiropoulos, P.[Panagiotis], Mezaris, V.[Vasileios], Kompatsiaris, I.[Ioannis],
Video Tomographs and a Base Detector Selection Strategy for Improving Large-Scale Video Concept Detection,
CirSysVideo(24), No. 7, July 2014, pp. 1251-1264.
IEEE DOI 1407
Accuracy BibRef

Zhao, G.Q.[Gang-Qiang], Yuan, J.S.[Jun-Song], Xu, J.[Jiang], Wu, Y.[Ying],
Discovering the Thematic Object in Commercial Videos,
MultMedMag(18), No. 3, 2011, pp. 56-65.
IEEE DOI 1108
BibRef

Sternig, S.[Sabine], Roth, P.M.[Peter M.], Bischof, H.[Horst],
On-line inverse multiple instance boosting for classifier grids,
PRL(33), No. 7, 1 May 2012, pp. 890-897.
Elsevier DOI 1203
BibRef
Earlier:
Learning of Scene-Specific Object Detectors by Classifier Co-Grids,
AVSS10(408-413).
IEEE DOI 1009
BibRef
And:
Inverse Multiple Instance Learning for Classifier Grids,
ICPR10(770-773).
IEEE DOI 1008
Award, ICPR. Classifier grids; On-line learning; AdaBoost; Object detection; Multiple instance learning BibRef

Roth, P.M.[Peter M.], Sternig, S.[Sabine], Grabner, H.[Helmut], Bischof, H.[Horst],
Classifier grids for robust adaptive object detection,
CVPR09(2727-2734).
IEEE DOI 0906
BibRef

Roth, P.M.[Peter M.], Grabner, H.[Helmut], Skocaj, D.[Danijel], Bischof, H.[Horst], Leonardis, A.[Aleš],
Conservative Visual Learning for Object Detection with Minimal Hand Labeling Effort,
DAGM05(293).
Springer DOI 0509

See also Learning Features for Tracking. BibRef

Roth, P.M.[Peter M.], Grabner, H.[Helmut], Bischof, H.[Horst], Skocaj, D.[Danijel], Leonardis, A.[Aleš],
On-line Conservative Learning for Person Detection,
PETS05(223-230).
IEEE DOI 0602
BibRef

Yuan, J., Zhao, G., Fu, Y., Li, Z., Katsaggelos, A.K., Wu, Y.,
Discovering Thematic Objects in Image Collections and Videos,
IP(21), No. 4, April 2012, pp. 2207-2219.
IEEE DOI 1204
BibRef

Dai, S.Y.[Sheng-Yang], Yang, M.[Ming], Wu, Y.[Ying], Katsaggelos, A.K.[Aggelos K.],
Detector Ensemble,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Gao, Y., Tang, J., Hong, R., Yan, S., Dai, Q., Zhang, N., Chua, T.S.,
Camera Constraint-Free View-Based 3-D Object Retrieval,
IP(21), No. 4, April 2012, pp. 2269-2281.
IEEE DOI 1204
BibRef

Tang, J., Zha, Z.J., Tao, D., Chua, T.S.,
Semantic-Gap-Oriented Active Learning for Multilabel Image Annotation,
IP(21), No. 4, April 2012, pp. 2354-2360.
IEEE DOI 1204
BibRef

Kim, J.S.[Jun-Seong], Sim, J.Y.[Jae-Young], Kim, C.S.[Chang-Su],
Multiscale Saliency Detection Using Random Walk With Restart,
CirSysVideo(24), No. 2, February 2014, pp. 198-210.
IEEE DOI 1403
Markov processes BibRef

Kim, J.S.[Jun-Seong], Kim, H.S.[Han-Sang], Sim, J.Y.[Jae-Young], Kim, C.S.[Chang-Su], Lee, S.U.[Sang-Uk],
Video saliency detection based on random walk with restart,
ICIP13(2465-2469)
IEEE DOI 1412
Markov chain BibRef

Chuang, C.H.[Chi-Han], Cheng, S.C.[Shyi-Chyi], Chang, C.C.[Chin-Chun], Chen, Y.P.P.[Yi-Ping Phoebe],
Model-based approach to spatial-temporal sampling of video clips for video object detection by classification,
JVCIR(25), No. 5, 2014, pp. 1018-1030.
Elsevier DOI 1406
Semantic video objects BibRef

Kim, W., Han, J.J.,
Video Saliency Detection Using Contrast of Spatiotemporal Directional Coherence,
SPLetters(21), No. 10, October 2014, pp. 1250-1254.
IEEE DOI 1407
Coherence BibRef

Zhu, Y.[Yukun], Zhu, J.[Jun], Zhang, R.[Rui],
Contextual Object Detection With Spatial Context Prototypes,
MultMed(16), No. 6, October 2014, pp. 1585-1596.
IEEE DOI 1410
data mining BibRef

Zhao, G.Q.[Gang-Qiang], Yuan, J.S.[Jun-Song], Hua, G.[Gang], Yang, J.[Jiong],
Topical Video Object Discovery from Key Frames by Modeling Word Co-occurrence Prior,
IP(24), No. 12, December 2015, pp. 5739-5752.
IEEE DOI 1512
Gaussian distribution BibRef
Earlier: A1, A2, A3, Only: CVPR13(1602-1609)
IEEE DOI 1309
An object frequently highlighted in a video. BibRef

Wang, B., Lin, D., Xiong, H., Zheng, Y.F.,
Joint Inference of Objects and Scenes With Efficient Learning of Text-Object-Scene Relations,
MultMed(18), No. 3, March 2016, pp. 507-520.
IEEE DOI 1603
Bicycles BibRef


Hartmann, G.[Glenn], Grundmann, M.[Matthias], Hoffman, J.[Judy], Tsai, D.[David], Kwatra, V.[Vivek], Madani, O.[Omid], Vijayanarasimhan, S.[Sudheendra], Essa, I.[Irfan], Rehg, J.[James], Sukthankar, R.[Rahul],
Weakly Supervised Learning of Object Segmentations from Web-Scale Video,
WebScale12(I: 198-208).
Springer DOI 1210
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Le, Q.V., Ranzato, M.A., Monga, R., Devin, M., Chen, K., Corrado, G.S., Dean, J., Ng, A.Y.,
Building high-level features using large scale unsupervised learning,
ICML12().
PDF File. 1209
Large scale deep learning simulations on 10000s of cores that lead to neurons for objects. BibRef

Le, Q.V., Karpenko, A., Ngiam, J., Ng, A.Y.,
ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning,
NIPS11(xx-yy). 1209

PDF File. BibRef

Sharir, G.[Gilad], Tuytelaars, T.[Tinne],
Video object proposals,
LSVSM12(9-14).
IEEE DOI 1207
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Blanchart, P.[Pierre], Ferecatu, M.[Marin], Datcu, M.[Mihai],
Cascaded active learning for object retrieval using multiscale coarse to fine analysis,
ICIP11(2793-2796).
IEEE DOI 1201
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Bursuc, A.[Andrei], Zaharia, T.[Titus], Prêteux, F.[Françoise],
Retrieval of Multiple Instances of Objects in Videos,
MMMod12(358-369).
Springer DOI 1201
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Costantini, L., Capodiferro, L., Carli, M., Neri, A.,
Impact of edges characterization on image clustering,
EUVIP10(237-240).
IEEE DOI 1110
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Shah, R.[Ronak], Iyer, R.[Rishabh], Chaudhuri, S.[Subhasis],
Object Mining for Large Video data,
BMVC11(xx-yy).
HTML Version. 1110
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Chen, B.C.[Bor-Chun], Wu, Z.X.[Zu-Xuan], Davis, L.S.[Larry S.], Lim, S.N.[Ser-Nam],
Efficient Object Embedding for Spliced Image Retrieval,
CVPR21(14960-14970)
IEEE DOI 2111
Training, Analytical models, Databases, Computational modeling, Image retrieval, Detectors BibRef

Lim, S.N.[Ser-Nam], Doretto, G.[Gianfranco], Rittscher, J.[Jens],
Multi-class Object Layout with Unsupervised Image Classification and Object Localization,
ISVC11(I: 573-585).
Springer DOI 1109
Persence of object class in image. BibRef

Lütz, A.[Alexander],
Robust Classification and Semi-supervised Object Localization with Gaussian Processes,
DAGM11(456-461).
Springer DOI 1109
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Qu, Y.Y.[Yan-Yun], Liu, H.[Han],
Visual Object Localization in Image Collections,
ICIG11(593-598).
IEEE DOI 1109
Context aware without labeled examples. Segment, then cluster to find the pattern. BibRef

Han, S.H.[Sun-Hyoung], Vasconcelos, N.M.[Nuno M.],
Biologically plausible detection of amorphous objects in the wild,
WBCV11(24-31).
IEEE DOI 1106
E.g. animals. Saliency tuned for object detection. BibRef

Sun, F.M.[Fu-Ming], Ge, Y.[Yong], Wang, D.X.[Dong-Xia], Wang, X.M.[Xue-Ming],
A Collaborative Approach for Image Annotation,
PSIVT10(192-196).
IEEE DOI 1011
Multiple statistical models. BibRef

Li, Z.D.[Zhi-Dong], Xu, J.[Jie], Wang, Y.[Yang], Geers, G.[Glenn], Yang, J.[Jun],
Saliency detection based on proto-objects and topic model,
WACV11(125-131).
IEEE DOI 1101

See also Feature fusion for vehicle detection and tracking with low-angle cameras. BibRef

Li, Z.D.[Zhi-Dong], Wang, Y.[Yang], Geers, G.[Glenn], Chen, J.[Jing], Yang, J.[Jun], Laird, J.[John],
Saliency based joint topic discovery for object categorization,
ICIP10(4581-4584).
IEEE DOI 1009
Foreground separation. Then categorize using both object and background. BibRef

Li, Z.D.[Zhi-Dong], Wang, Y.[Yang], Chen, J.[Jing], Xu, J.[Jie], Larid, J.[John],
Image Topic Discovery with Saliency Detection,
BMVC10(xx-yy).
HTML Version. 1009
Salient objects. BibRef

Jiang, X.Q.[Xiao-Qian], Wu, Q.[Qi], Tao, P.[Peng], Sweeney, L.[Latanya],
Structure preserving semantic coherent object segmentation,
ICIP10(2209-2212).
IEEE DOI 1009
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Ma, J.[Jun], Zheng, L.[Long], Yaguchi, Y.[Yuichi], Dong, M.X.[Mian-Xiong], Oka, R.[Ryuichi],
Image classification based on segmentation-free object recognition,
ICIP10(2157-2160).
IEEE DOI 1009
BibRef

Wang, S.C.[Shao-Chuan], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
A Multi-Scale Learning Framework for Visual Categorization,
ACCV10(I: 310-322).
Springer DOI 1011
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Wang, S.C.[Shao-Chuan], Wang, Y.C.F.,
Simultaneous Object Recognition and Localization in Image Collections,
AVSS10(497-504).
IEEE DOI 1009
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Xie, B.[Bo], Song, M.L.[Ming-Li], Tao, D.C.[Da-Cheng],
Large-scale Dictionary Learning for Local Coordinate Coding,
BMVC10(xx-yy).
HTML Version. 1009
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Khuwuthyakorn, P.[Pattaraporn], Robles-Kelly, A.[Antonio], Zhou, J.[Jun],
Object of Interest Detection by Saliency Learning,
ECCV10(II: 636-649).
Springer DOI 1009
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Wang, G.[Gang], Forsyth, D.A.[David A.],
Joint learning of visual attributes, object classes and visual saliency,
ICCV09(537-544).
IEEE DOI 0909
Attribute: red, metal, ... class: Car, ... Images labeled with category, but not location. BibRef

Vu, C.T.[Cuong T.], Chandler, D.M.[Damon M.],
An algorithm for detecting multiple salient objects in images via adaptive feature selection,
ICIP12(657-660).
IEEE DOI 1302
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Earlier:
Main subject detection via adaptive feature selection,
ICIP09(3101-3104).
IEEE DOI 0911
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Jiang, A.[Aiwen], Wang, C.H.[Chun-Heng], Xiao, B.H.[Bai-Hua],
Scene modeling in global-local view for scene classification,
CIVR08(179-184). 0807
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Laungrungthip, N., McKinnon, A.E., Churcher, C.D., Unsworth, K.,
Edge-based detection of sky regions in images for solar exposure prediction,
IVCNZ08(1-6).
IEEE DOI 0811
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Shoemaker, L.[Larry], Banfield, R.E.[Robert E.], Hall, L.O.[Lawrence O.], Bowyer, K.W.[Kevin W.], Kegelmeyer, W.P.[W. Philip],
Detecting and ordering salient regions for efficient browsing,
ICPR08(1-4).
IEEE DOI 0812
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Le Hégarat-Mascle, S., Robin, A., Reynaud, R.,
Simultaneous localization and object detection using an a-contrario approach,
ICCVGIP10(440-447).
DOI Link 1111
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Ammar, M., Le Hegarat-Mascle, S., Reynaud, R., Robin, A.,
Video Scene Object Detection Using An A Contrario Approach,
IPTA08(1-8).
IEEE DOI 0811
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Pujol, A., Chen, L.,
Coarse adaptive color image segmentation for visual object classification,
WSSIP08(157-160).
IEEE DOI 0806
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Patterson, A.I.[Alexander I.], Mordohai, P.[Philippos], Daniilidis, K.[Kostas],
Object Detection from Large-Scale 3D Datasets Using Bottom-Up and Top-Down Descriptors,
ECCV08(IV: 553-566).
Springer DOI 0810
BibRef

Cui, J.Y.[Jing-Yu], Yang, Q.[Qiong], Wen, F.[Fang], Wu, Q.Y.[Qi-Ying], Zhang, C.S.[Chang-Shui], Van Gool, L.J.[Luc J.], Tang, X.[Xiaoou],
Transductive object cutout,
CVPR08(1-8).
IEEE DOI 0806
While object and background may share colors, they rarely share color configurations. BibRef

Ma, X.X.[Xiao-Xu], Grimson, W.E.L.[W. Eric L.],
Learning coupled conditional random field for image decomposition with application on object categorization,
CVPR08(1-8).
IEEE DOI 0806
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Masnadi-Shirazi, H.[Hamed], Vasconcelos, N.M.[Nuno M.],
High Detection-rate Cascades for Real-Time Object Detection,
ICCV07(1-6).
IEEE DOI 0710
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Zhang, W.[Wei], Zelinsky, G.J.[Gregory J.], Samaras, D.[Dimitris],
Real-time Accurate Object Detection using Multiple Resolutions,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Ma, J.[Jie], Lu, H.[Hong], Guo, Y.F.[Yue-Fei],
Region Based Image Retrieval Incorporated with Camera Metadata,
Visual07(84-92).
Springer DOI 0706
BibRef

Zhang, W.[Wei], Xue, X.Y.[Xiang-Yang], Sun, Z.C.[Zi-Chen], Guo, Y.F.[Yue-Fei], Chi, M.M.[Ming-Min], Lu, H.[Hong],
Efficient Feature Extraction for Image Classification,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Yu, X., Yi, L.,
Object Detection Using Shape Codebook,
BMVC07(xx-yy).
PDF File. 0709
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Wang, L.M.[Li-Ming], Shi, J.B.[Jian-Bo], Song, G.[Gang], Shen, I.F.[I-Fan],
Object Detection Combining Recognition and Segmentation,
ACCV07(I: 189-199).
Springer DOI 0711
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Huart, J.[Jeremy], Bertolino, P.[Pascal],
A Generic Process Chain to Extract Key-Objects from Video Shots,
ICIP07(VI: 305-308).
IEEE DOI 0709
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Gao, S.[Sheng], Lim, J.H.[Joo-Hwee],
Selecting representative and distinctive descriptors for efficient landmark recognition,
ICIP09(1425-1428).
IEEE DOI 0911
Choosing important features for categorization. BibRef

Gao, S.[Sheng], Lim, J.H.[Joo-Hwee], Sun, Q.B.[Qi-Bin],
Propagating Image-Level Part Statistics to Enhance Object Detection,
ICIP07(VI: 181-184).
IEEE DOI 0709
BibRef

Bianchi, L.[Luca], Martinelli, A.[Alessandro],
A Clustering Approach to Object Estimation, Featuring Image Filtering Prototyping for DBSCAN in Virtual Sets,
CIAP07(751-756).
IEEE DOI 0709
Filter data before clustering. BibRef

Wu, Y.[Yang], Zhu, Q.H.[Qi-Hui], Shi, J.B.[Jian-Bo], Zheng, N.N.[Nan-Ning],
Saliency Based Opportunistic Search for Object Part Extraction and Labeling,
ECCV08(IV: 760-774).
Springer DOI 0810
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Lu, Y.[Yao], Zhang, W.[Wei], Lu, H.[Hong], Xue, X.Y.[Xiang-Yang],
Salient Object Detection using concavity context,
ICCV11(233-240).
IEEE DOI 1201
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Zhang, S.L.[Shi-Le], Fan, J.P.[Jian-Ping], Lu, H.[Hong], Xue, X.Y.[Xiang-Yang],
Salient Object Detection on Large-Scale Video Data,
SLAM07(1-6).
IEEE DOI 0706
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Romdhani, S.[Sami], Vetter, T.[Thomas],
3D Probabilistic Feature Point Model for Object Detection and Recognition,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Yuan, Q.[Quan], Thangali, A.[Ashwin], Ablavsky, V.[Vitaly], Sclaroff, S.[Stan],
Parameter Sensitive Detectors,
CVPR07(1-6).
IEEE DOI 0706
BibRef

Cho, M.S.[Min-Su], Lee, K.M.[Kyoung Mu],
Partially Occluded Object-Specific Segmentation in View-Based Recognition,
CVPR07(1-7).
IEEE DOI 0706
BibRef

Ramanan, D.[Deva],
Using Segmentation to Verify Object Hypotheses,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Vasquez, D., Romanelli, F., Fraichard, T., Laugier, C.,
Fast Object Extraction from Bayesian Occupancy Grids using Self Organizing Networks,
ICARCV06(1-6).
IEEE DOI 0612
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Wang, T.[Tsaipei],
Possibilistic C-Template Clustering and Its Application in Object Detection in Images,
PSIVT06(383-392).
Springer DOI 0612
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Sluzek, A.[Andrzej],
Extended Keypoint Description and the Corresponding Improvements in Image Retrieval,
RoLoD14(698-709).
Springer DOI 1504

See also Detection of Near-Duplicate Patches in Random Images Using Keypoint-Based Features. BibRef

Sluzek, A.[Andrzej],
Approximation-Based Keypoints in Colour Images: A Tool for Building and Searching Visual Databases,
Visual07(5-16).
Springer DOI 0706

See also Building Local Features from Pattern-Based Approximations of Patches: Discussion on Moments and Hough Transform. BibRef

Takahashi, Y., Hirata, K.,
Segmented-Region Based Approach Using Object Components Database to Detect Sky Region,
ICIP06(2733-2736).
IEEE DOI 0610
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Le, D.D.[Duy-Dinh], Satoh, S.[Shin'ichi],
Robust Object Detection using Fast Feature Selection from Huge Feature Sets,
ICIP06(961-964).
IEEE DOI 0610
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Zafarifar, B.[Bahman], de With, P.H.N.[Peter H. N.],
Grass Detection for Picture Quality Enhancement of TV Video,
ACIVS07(687-698).
Springer DOI 0708
BibRef

Zafarifar, B.[Bahman], de With, P.H.N.[Peter H. N.],
Blue Sky Detection for Picture Quality Enhancement,
ACIVS06(522-532).
Springer DOI 0609
BibRef

Gao, L., Jiang, J., Yang, S.Y.,
Constrained Region-Growing and Edge Enhancement Towards Automated Semantic Video Object Segmentation,
ACIVS06(323-331).
Springer DOI 0609
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Yang, J.Y.[Jun-Yeong], Byun, H.R.[Hye-Ran],
A Combination of Generative and Discriminative Approaches to Object Detection,
ICPR06(III: 249-253).
IEEE DOI 0609
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Ko, B.C.[Byoung Chul], Nam, J.Y.[Jae-Yeal],
Automatic Object-of-Interest segmentation from natural images,
ICPR06(IV: 45-48).
IEEE DOI 0609
BibRef

Ko, B.C.[Byoung Chul], Kwak, S.Y.[Soo Yeong], Byun, H.R.[Hye-Ran],
SVM-based salient region(s) extraction method for image retrieval,
ICPR04(II: 977-980).
IEEE DOI 0409
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Zhao, Z.P.[Zhi-Peng], Elgammal, A.M.[Ahmed M.],
A Statistically Selected Part-Based Probabilistic Model for Object Recognition,
IWICPAS06(95-104).
Springer DOI 0608
Select image patches that correspond to the object, not the background. BibRef

Tsai, Y.T.J.[Yao-Tsung Jason], Lien, J.J.J.[Jenn-Jier James],
Efficient Object Segmentation Using Digital Matting for MPEG Video Sequences,
ACCV06(II:591-601).
Springer DOI 0601
BibRef

Kutics, A.[Andrea], Nakagawa, A.[Akihiko],
Naming of Image Regions for User-Friendly Image Retrieval,
ICIAR06(I: 612-623).
Springer DOI 0610
BibRef
Earlier:
Detecting Prominent Objects for Image Retrieval,
ICIP05(III: 445-448).
IEEE DOI 0512
BibRef
Earlier:
Semantic Browsing and Retrieval in Image Libraries,
ICIAR04(I: 737-744).
Springer DOI 0409
BibRef

Cheng, L.S.[Li-Shui], Yang, J.[Jie], Fan, X.[Xian],
A New Region-Based Active Contour for Object Extraction Using Level Set Method,
IbPRIA05(I:285).
Springer DOI 0509
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Kumar, M.P.[M. Pawan], Torr, P.H.S.[Philip H. S.], Zisserman, A.,
Obj Cut,
CVPR05(I: 18-25).
IEEE DOI 0507
Detect and Segment instances of a particular object in an image. BibRef

Bourdev, L.[Lubomir], Brandt, J.[Jonathan],
Robust Object Detection via Soft Cascade,
CVPR05(II: 236-243).
IEEE DOI 0507
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Traver, V.J.[V. Javier], Bernardino, A.[Alexandre], Moreno, P.[Plinio], Santos-Victor, J.[José],
Appearance-Based Object Detection in Space-Variant Images: A Multi-model Approach,
ICIAR04(I: 538-546).
Springer DOI 0409

See also Dealing with 2D translation estimation in log-polar imagery. BibRef

Fang, J.Z.[Jian-Zhong], Qiu, G.P.[Guo-Ping],
Learning an Information Theoretic Transform for Object Detection,
ICIAR04(I: 503-510).
Springer DOI 0409
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Wang, J.X.[Jun-Xian], Eng, H.L.[How-Lung], Kam, A.H.[Alvin H.], Yau, W.Y.[Wei-Yun],
A Framework for Foreground Detection in Complex Environments,
SMVP04(129-140).
Springer DOI 0505
BibRef

Fan, X.D.[Xiao-Dong],
Contextual disambiguation for multi-class object detection,
ICIP04(V: 2873-2876).
IEEE DOI 0505
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Rymel, J., Renno, J.P., Greenhill, D.R.[Darrel R.], Orwell, J., Jones, G.A.,
Adaptive eigen-backgrounds for object detection,
ICIP04(III: 1847-1850).
IEEE DOI 0505
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Treetasonatavorn, S., Heuer, J., Rauschenbach, U., Illgner, K., Kaup, A.,
Temporal video segmentation using global motion estimation and discrete curve evolution,
ICIP04(I: 385-388).
IEEE DOI 0505
Temporal video segmentation based on global motion. BibRef

Stepleton, T.[Thomas], Lee, T.S.[Tai Sing],
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video,
WACV05(I: 129-134).
IEEE DOI 0502
Regularly co-occuring features tend to be from the object. BibRef

Stepleton, T.S.,
Predicting and Evaluating the Power of Shared Features,
EEMCV05(III: 39-39).
IEEE DOI 0507
BibRef

Li, S.G.[Shi-Gang],
Sky-ground representation for local scene description,
ICPR04(III: 252-255).
IEEE DOI 0409
BibRef

Zang, Q.[Qi], Klette, R.,
Robust background subtraction and maintenance,
ICPR04(II: 90-93).
IEEE DOI 0409
BibRef

Ramstrom, O., Christensen, H.I.,
Object detection using background context,
ICPR04(III: 45-48).
IEEE DOI 0409
BibRef

Levi, K., Weiss, Y.,
Learning Object Detection from a Small Number of Examples: The Importance of Good Features,
CVPR04(II: 53-60).
IEEE DOI 0408
BibRef

Han, J.W.[Jun-Wei], Li, M.J.[Ming-Jing], Zhang, H.J.[Hong-Jiang], Guo, L.[Lei],
Automatic attention object extraction from images,
ICIP03(II: 403-406).
IEEE DOI 0312
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Saitoh, T.[Takeshi], Aoki, K.[Kimiya], Kaneko, T.[Toyohisa],
Automatic Extraction of Object Region from Photographs,
SCIA03(1130-1137).
Springer DOI 0310
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Xiao, R.[Rong], Zhu, L.[Long], Zhang, H.J.[Hong-Jiang],
Boosting chain learning for object detection,
ICCV03(709-715).
IEEE DOI 0311
BibRef

Lienhart, R.[Rainer], Kuranov, A.[Alexander], Pisarevsky, V.[Vadim],
Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection,
DAGM03(297-304).
Springer DOI 0310
BibRef

Paletta, L.[Lucas], Greindl, C.[Christian],
Context Based Object Detection from Video,
CVS03(502 ff).
Springer DOI 0306
BibRef

Li, Y.[Yi], Shapiro, L.G.,
Consistent line clusters for building recognition in CBIR,
ICPR02(III: 952-956).
IEEE DOI 0211
BibRef

Hamker, F.H.[Fred H.], Worcester, J.[James],
Object Detection in Natural Scenes by Feedback,
BMCV02(398 ff.).
Springer DOI 0303
BibRef

Cheoi, K.J.[Kyung-Joo], Lee, Y.B.[Yill-Byung],
A Method of Extracting Objects of Interest with Possible Broad Application in Computer Vision,
BMCV02(331 ff.).
Springer DOI 0303
BibRef

Luo, Y.[Ye], Tian, Q.[Qi],
Spatio-temporal enhanced sparse feature selection for video saliency estimation,
LSVSM12(33-38).
IEEE DOI 1207
BibRef

Li, L.Y.[Li-Yuan], Huang, W.M.[Wei-Min], Gu, I.Y.H., Tian, Q.[Qi],
Foreground object detection in changing background based on color co-occurrence statistics,
WACV02(269-274).
IEEE DOI 0303
BibRef

Pardo, A.,
Extraction of semantic objects from still images,
ICIP02(III: 305-308).
IEEE DOI 0210
BibRef

Mezaris, V., Kompatsiaris, I., Strintzis, M.C.,
A framework for the efficient segmentation of large-format color images,
ICIP02(I: 761-764).
IEEE DOI 0210
Find the main object. BibRef

Jin, H., Sakauchi, M.,
Content-based Objects Detection for the Recognition of Building Images,
ICIP01(II: 705-708).
IEEE DOI 0108
BibRef

Satoh, S., Idehara, Y., Mo, H., Hamada, T.,
Subject Region Segmentation in Disparity Maps for Image Retrieval,
ICIP01(II: 725-728).
IEEE DOI 0108
BibRef

Raghunathan, B.,
Area Morphological Segmentation for Content Based Retrieval,
ICIP00(Vol III: 738-741).
IEEE DOI 0008
BibRef

Ramamoorthy, A.,
An Integrated Segmentation Technique for Interactive Image Retrieval,
ICIP00(Vol III: 762-765).
IEEE DOI 0008
BibRef

Srihari, R.K., Zhang, Z., Rao, A.,
Image Background Search: Combining Object Detection Techniques with Content-Based Image Retrieval (CBIR) Systems,
CBAIVL99(xx-yy). BibRef 9900

Winter, A., Nastar, C.,
Differential Feature Distribution Maps for Image Segmentation and Region Queries in Image Databases,
CBAIVL99(xx-yy). BibRef 9900

Lu, Y.[Yi], Guo, H.[Hong],
Background removal in image indexing and retrieval,
CIAP99(933-938).
IEEE DOI 9909
BibRef

Maeda, E., Tanaka, H., Shio, A., Ishii, K.,
Robust object extraction using normalized principal component features,
ICPR92(III:151-155).
IEEE DOI 9208
BibRef

Hanusse, P.[Patrick], Guillataud, P.[Philippe],
Object detection and identification by hierarchical segmentation,
ECCV90(583-585).
Springer DOI 9004
BibRef

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Video Database Issues and Techniques .


Last update:Mar 16, 2024 at 20:36:19