18.3.4 Extract Moving Objects from Image Sequences or Video

Chapter Contents (Back)
Motion, Segmentation. Segmentation, Motion. Object Segmentation. Sequence Analysis. Motion Segmentation. See also Motion Segmentation by Tracking, Trajectories, Region Based Tracking. Edge based: See also Moving Object Extraction Using Edges. See also Range and Color, RGB-D Segmentation and Analysis.

Mutch, K.M.[Kathleen M.], and Thompson, W.B.[William B.],
Analysis of Accretion and Deletion at Boundaries in Dynamic Scenes,
PAMI(7), No. 2, March 1985, pp. 133-138. BibRef 8503
Earlier: Univ. of MinnesotaTR 84-7, Computer Science Dept, May 1984. Analysis of the changes (adding and removing) in regions at boundaries when one object moves relative to the other. This can give the optic flow data for the region near the boundary. BibRef

Thompson, W.B.,
Combining Motion and Contrast for Segmentation,
PAMI(2), No. 6, November 1980, pp. 543-549. Brightness is used for static segmentation then merge regions based on motion similarities. See also Velocity Determination in Scenes Containing Several Moving Objects. BibRef 8011

Thompson, W.B., and Pong, T.C.,
Detecting Moving Objects,
IJCV(4), No. 1. January 1990, pp. 39-58.
Springer DOI BibRef 9001
Earlier: ICCV87(201-208). Several different restricted techniques are developed for motion detection using camera motion or scene structure and flow fields. BibRef

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

Castellano, G.[Gabriela], Boyce, J.[James], Sandler, M.[Mark],
Regularized CDWT optical flow applied to moving-target detection in IR imagery,
MVA(11), No. 6, 2000, pp. 277-288.
Springer DOI 0005
BibRef
Earlier:
Moving Target Detection in Infrared Imagery Using a Regularised CDWT Optical Flow,
CVBVS99(13).
IEEE DOI 9906
BibRef

Sarkar, S.[Sudeep], Majchrzak, D.[Daniel], Korimilli, K.[Kishore],
Perceptual Organization Based Computational Model for Robust Segmentation of Moving Objects,
CVIU(86), No. 3, June 2002, pp. 141-170.
DOI Link 0301
BibRef
Earlier: A3, A1, Only:
Motion Segmentation Based on Perceptual Organization of Spatio-temporal Volumes,
ICPR00(Vol III: 844-849).
IEEE DOI 0009
BibRef

Tuncel, E., Onural, L.,
Utilization of the Recursive Shortest Spanning Tree Algorithm for Video Object Segmentation by 2-D Affine Motion Modeling,
CirSysVideo(10), No. 5, August 2000, pp. 776-781.
IEEE Top Reference. 0008
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

Zhang, X.P.[Xiao-Ping], Chen, Z.[Zhenhe],
An Automated Video Object Extraction System Based on Spatiotemporal Independent Component Analysis and Multiscale Segmentation,
JASP(2006), 2006, pp. 1-22.
WWW Link. 0603
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
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

Dosil, R.[Raquel], Fdez-Vidal, X.R.[Xose R.], Pardo, X.M.[Xose M.],
Motion representation using composite energy features,
PR(41), No. 3, March 2008, pp. 1110-1123.
Elsevier DOI 0711
See also Distances between frequency features for 3D visual pattern partitioning. Spatio-temporal energy filtering; Feature integration; Composite energy features; Apparent-motion segmentation and tracking BibRef

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

Qi, B.[Bin], Ghazal, M.[Mohammed], Amer, A.[Aishy],
Robust Global Motion Estimation Oriented to Video Object Segmentation,
IP(17), No. 6, June 2008, pp. 958-967.
IEEE DOI 0711
BibRef
Earlier: A1, A3, Only:
Robust and Fast Global Motion Estimation Oriented to Video Object Segmentation,
ICIP05(I: 153-156).
IEEE DOI 0512
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

Yang, H.[Hong], Tian, J.W.[Jin-Wen], Chu, Y., Tang, Q., Liu, J.[Jian],
Spatiotemporal Smooth Models for Moving Object Detection,
SPLetters(15), No. 1, 2008, pp. 497-500.
IEEE DOI 0806
BibRef

Li, Y.S.[Yan-Sheng], Tan, Y.H.[Yi-Hua], Yu, J.G.[Jin-Gang], Qi, S.X.[Sheng-Xiang], Tian, J.W.[Jin-Wen],
Kernel regression in mixed feature spaces for spatio-temporal saliency detection,
CVIU(135), No. 1, 2015, pp. 126-140.
Elsevier DOI 1504
Spatio-temporal saliency BibRef

Yang, H.[Hong], Tan, Y.H.[Yi-Hua], Tian, J.W.[Jin-Wen], Liu, J.[Jian],
Accurate Dynamic Scene Model for Moving Object Detection,
ICIP07(VI: 157-160).
IEEE DOI 0709
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

Gryn, J.M.[Jacob M.], Wildes, R.P.[Richard P.], Tsotsos, J.K.[John K.],
Detecting Motion Patterns via Direction Maps with Application to Surveillance,
CVIU(113), No. 2, February 2009, pp. 291-307.
Elsevier DOI 0901
BibRef
And: WACV05(I: 202-209).
IEEE DOI 0502
Surveillance; Direction maps; Dominant direction; Event detection; Spatiotemporal analysis; Motion analysis 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

Wu, B.[Bo], Nevatia, R.[Ram],
Detection and Segmentation of Multiple, Partially Occluded Objects by Grouping, Merging, Assigning Part Detection Responses,
IJCV(82), No. 2, April 2009, pp. xx-yy.
Springer DOI 0903
BibRef
Earlier:
Optimizing discrimination-efficiency tradeoff in integrating heterogeneous local features for object detection,
CVPR08(1-8).
IEEE DOI
PDF File. 0806
See also Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors. BibRef

Wu, B.[Bo], Nevatia, R.[Ram], Li, Y.[Yuan],
Segmentation of multiple, partially occluded objects by grouping, merging, assigning part detection responses,
CVPR08(1-8).
IEEE DOI
PDF File. 0806
BibRef

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

Guan, Y.P.,
Spatio-temporal motion-based foreground segmentation and shadow suppression,
IET-CV(4), No. 1, March 2010, pp. 50-60.
DOI Link 1001
BibRef

Luo, Y.[Yong], Guan, Y.P.[Ye Peng],
Motion objects segmentation based on structural similarity background modelling,
IET-CV(9), No. 4, 2015, pp. 476-488.
DOI Link 1509
computer vision 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

Engin, E.[Erman], Özcan, M.[Meriç],
Moving target detection using super-resolution algorithms with an ultra wideband radar,
IJIST(20), No. 3, September 2010, pp. 237-244.
DOI Link 1008
BibRef

Zappella, L.[Luca], Llado, 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, 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], Provenzi, E., Lladó, X.[Xavier], Salvi, J.[Joaquim],
Adaptive Motion Segmentation Algorithm Based on the Principal Angles Configuration,
ACCV10(III: 15-26).
Springer DOI 1011
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

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

Xu, J.[Jiang], Yuan, J.S.[Jun-Song], Wu, Y.[Ying],
Learning spatio-temporal dependency of local patches for complex motion segmentation,
CVIU(115), No. 3, March 2011, pp. 334-351.
Elsevier DOI 1103
Motion segmentation; Learning; Motion profile symmetry correlation; Bipolar segmentation BibRef

Wedel, A.[Andreas], Brox, T.[Thomas], Vaudrey, T.[Tobi], Rabe, C.[Clemens], Franke, U.[Uwe], Cremers, D.[Daniel],
Stereoscopic Scene Flow Computation for 3D Motion Understanding,
IJCV(95), No. 1, October 2011, pp. 29-51.
WWW Link. 1108
BibRef
Earlier: A1, A4, A3, A2, A5, A6:
Efficient Dense Scene Flow from Sparse or Dense Stereo Data,
ECCV08(I: 739-751).
Springer DOI 0810
See also Video Super Resolution Using Duality Based TV-L1 Optical Flow. BibRef

Ochs, P., Malik, J., Brox, T.,
Segmentation of Moving Objects by Long Term Video Analysis,
PAMI(36), No. 6, June 2014, pp. 1187-1200.
IEEE DOI 1406
Adaptive optics BibRef

Quiroga, J.[Julian], Brox, T.[Thomas], Devernay, F.[Frédéric], Crowley, J.L.[James L.],
Dense Semi-rigid Scene Flow Estimation from RGBD Images,
ECCV14(VII: 567-582).
Springer DOI 1408
BibRef

Ochs, P.[Peter], Brox, T.[Thomas],
Higher order motion models and spectral clustering,
CVPR12(614-621).
IEEE DOI 1208
BibRef
And:
Object segmentation in video: A hierarchical variational approach for turning point trajectories into dense regions,
ICCV11(1583-1590).
IEEE DOI 1201
BibRef

Brox, T.[Thomas], Malik, J.[Jitendra],
Object Segmentation by Long Term Analysis of Point Trajectories,
ECCV10(V: 282-295).
Springer DOI 1009
BibRef

Wedel, A.[Andreas], Cremers, D.[Daniel],
Stereo Scene Flow for 3D Motion Analysis,
Springer2011. ISBN: 978-0-85729-964-2.
WWW Link. 1109
BibRef

Wedel, A., Pock, T., Braun, J., Franke, U., Cremers, D.,
Duality TV-L1 flow with fundamental matrix prior,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Klappstein, J.[Jens], Vaudrey, T.[Tobi], Rabe, C.[Clemens], Wedel, A.[Andreas], Klette, R.[Reinhard],
Moving Object Segmentation Using Optical Flow and Depth Information,
PSIVT09(611-623).
Springer DOI 0901
BibRef
Earlier: A2, A4, A3, A1, A5:
Evaluation of moving object segmentation comparing 6D-vision and monocular motion constraints,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Wedel, A.[Andreas], Meißner, A.[Annemarie], Rabe, C.[Clemens], Franke, U.[Uwe], Cremers, D.[Daniel],
Detection and Segmentation of Independently Moving Objects from Dense Scene Flow,
EMMCVPR09(14-27).
Springer DOI 0908
BibRef

Klappstein, J.[Jens], Stein, F.[Fridtjof], Franke, U.[Uwe],
Detectability of Moving Objects Using Correspondences over Two and Three Frames,
DAGM07(112-121).
Springer DOI 0709
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

Sekmen, A., Aldroubi, A.,
Subspace and motion segmentation via local subspace estimation,
WORV13(27-33)
IEEE DOI 1307
image matching BibRef

Yi, Y.[Yang], Ding, J.[Jia], Lai, J.L.[Jie-Ling],
A novel video salient object extraction method based on visual attention,
SP:IC(28), No. 1, January 2013, pp. 45-54.
Elsevier DOI 1301
Video object segmentation; Salient object extraction; Visual attention model; Attention object growing BibRef

Li, R.N.[Ruo-Nan], Chellappa, R.[Rama],
Spatiotemporal Alignment of Visual Signals on a Special Manifold,
PAMI(35), No. 3, March 2013, pp. 697-715.
IEEE DOI 1303
BibRef
Earlier:
Aligning Spatio-Temporal Signals on a Special Manifold,
ECCV10(V: 547-560).
Springer DOI 1009
BibRef
And:
Group motion segmentation using a Spatio-Temporal Driving Force Model,
CVPR10(2038-2045).
IEEE DOI 1006
BibRef

Belardinelli, A.[Anna], Carbone, A.[Andrea], Schneider, W.X.[Werner X.],
Classification of multiscale spatiotemporal energy features for video segmentation and dynamic objects prioritisation,
PRL(34), No. 7, 1 May 2013, pp. 713-722.
Elsevier DOI 1303
Video segmentation; Spatiotemporal features; Visual attention; Object-based saliency 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.[Yibin], Cai, C.[Canhui], 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.[Dawei], 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

Li, Y., Sheng, B., Ma, L., Wu, W., Xie, Z.,
Temporally Coherent Video Saliency Using Regional Dynamic Contrast,
CirSysVideo(23), No. 12, 2013, pp. 2067-2076.
IEEE DOI 1312
Computational efficiency. Region-based visual dynamic contrast. BibRef

Han, J., He, S., Qian, X., Wang, D., Guo, L., Liu, T.,
An Object-Oriented Visual Saliency Detection Framework Based on Sparse Coding Representations,
CirSysVideo(23), No. 12, 2013, pp. 2009-2021.
IEEE DOI 1312
Computer vision BibRef

Wu, B.[Bo], Xu, L.F.[Lin-Feng], Zeng, L.Y.[Liao-Yuan], Wang, Z.N.[Zheng-Ning], Wang, Y.[Yan],
A unified framework for spatiotemporal salient region detection,
JIVP(2013), No. 1, 2013, pp. 16.
DOI Link 1305
BibRef

Li, W.T.[Wei-Te], Chang, H.S.[Haw-Shiuan], Lien, K.C.[Kuo-Chin], Chang, H.T.[Hui-Tang], Wang, Y.F.,
Exploring Visual and Motion Saliency for Automatic Video Object Extraction,
IP(22), No. 7, 2013, pp. 2600-2610.
IEEE DOI conditional random field; foreground object extraction; foreground-background region separation; visual saliency 1307
BibRef

Li, W.T.[Wei-Te], Chang, H.T.[Hui-Tang], Lyu, H.S.[Hermes Shing], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Automatic saliency inspired foreground object extraction from videos,
ICIP12(1089-1092).
IEEE DOI 1302
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

Barranco, F.[Francisco], Fermuller, C., Aloimonos, Y.,
Contour Motion Estimation for Asynchronous Event-Driven Cameras,
PIEEE(102), No. 10, October 2014, pp. 1537-1556.
IEEE DOI 1410
computer vision BibRef

Barranco, F.[Francisco], Teo, C.L., Fermuller, C., Aloimonos, Y.,
Contour Detection and Characterization for Asynchronous Event Sensors,
ICCV15(486-494)
IEEE DOI 1602
Computer vision 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

Ma, X., Najjar, W.A., Roy-Chowdhury, A.K.,
Evaluation and Acceleration of High-Throughput Fixed-Point Object Detection on FPGAs,
CirSysVideo(25), No. 6, June 2015, pp. 1051-1062.
IEEE DOI 1506
Accuracy BibRef

Rahmati, H.[Hodjat], Dragon, R.[Ralf], Aamo, O.M.[Ole Morten], Adde, L.[Lars], Stavdahl, Ř.[Řyvind], 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

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Shao, L.[Ling],
Consistent Video Saliency Using Local Gradient Flow Optimization and Global Refinement,
IP(24), No. 11, November 2015, pp. 4185-4196.
IEEE DOI 1509
gradient methods BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Shao, L.[Ling], Porikli, F.[Fatih],
Correspondence Driven Saliency Transfer,
IP(25), No. 11, November 2016, pp. 5025-5034.
IEEE DOI 1610
BibRef
Earlier: A1, A2, A4, Only:
Saliency-aware geodesic video object segmentation,
CVPR15(3395-3402)
IEEE DOI 1510
estimation theory. 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

Ortego, D.[Diego], San Miguel, J.C.[Juan C.], Martínez, J.M.[José M.],
Long-Term Stationary Object Detection Based on Spatio-Temporal Change Detection,
SPLetters(22), No. 12, December 2015, pp. 2368-2372.
IEEE DOI 1512
feature extraction BibRef

Chen, C.Z.[Chengli-Zhao], Li, S.[Shuai], Qin, H.[Hong], Hao, A.[Aimin],
Robust salient motion detection in non-stationary videos via novel integrated strategies of spatio-temporal coherency clues and low-rank analysis,
PR(52), No. 1, 2016, pp. 410-432.
Elsevier DOI 1601
Salient motion detection BibRef

Chen, C.Z.[Chengli-Zhao], Li, S.[Shuai], Wang, Y., Qin, H.[Hong], Hao, A.[Aimin],
Video Saliency Detection via Spatial-Temporal Fusion and Low-Rank Coherency Diffusion,
IP(26), No. 7, July 2017, pp. 3156-3170.
IEEE DOI 1706
Cameras, Computational modeling, Feature extraction, Image color analysis, Motion detection, Robustness, Video sequences, Spatial-temporal saliency fusion, low-rank coherency guided saliency diffusion, video saliency, visual, saliency BibRef

Yang, J., Price, B., Shen, X., Lin, Z., Yuan, J.,
Fast Appearance Modeling for Automatic Primary Video Object Segmentation,
IP(25), No. 2, February 2016, pp. 503-515.
IEEE DOI 1601
Adaptation models 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

Yang, J., Zhao, G., Yuan, J., Shen, X., Lin, Z., Price, B., Brandt, J.,
Discovering Primary Objects in Videos by Saliency Fusion and Iterative Appearance Estimation,
CirSysVideo(26), No. 6, June 2016, pp. 1070-1083.
IEEE DOI 1606
Estimation 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

Rochan, M.[Mrigank], Rahman, S.[Shafin], Bruce, N.D.B.[Neil D.B.], Wang, Y.[Yang],
Weakly supervised object localization and segmentation in videos,
IVC(56), No. 1, 2016, pp. 1-12.
Elsevier DOI 1609
Weakly supervised BibRef
Earlier:
Segmenting Objects in Weakly Labeled Videos,
CRV14(119-126)
IEEE DOI 1406
Computational modeling BibRef

Rochan, M.[Mrigank], Wang, Y.[Yang],
Latent SVM for Object Localization in Weakly Labeled Videos,
CRV15(200-207)
IEEE DOI 1507
BibRef
Earlier:
Efficient Object Localization and Segmentation in Weakly Labeled Videos,
ISVC14(I: 172-181).
Springer DOI 1501
Birds BibRef

Wang, Y.H.[Yu-Hang], Liu, J.[Jing], Li, Y.[Yong], Fu, J.[Jun], Xu, M.[Min], Lu, H.Q.[Han-Qing],
Hierarchically Supervised Deconvolutional Network for Semantic Video Segmentation,
PR(64), No. 1, 2017, pp. 437-445.
Elsevier DOI 1701
Semantic video segmentation BibRef

Galteri, L., Seidenari, L.[Lorenzo], Bertini, M., del Bimbo, A.[Alberto],
Spatio-Temporal Closed-Loop Object Detection,
IP(26), No. 3, March 2017, pp. 1253-1263.
IEEE DOI 1703
computer vision BibRef

Cuffaro, G.[Giovanni], Becattini, F.[Federico], Baecchi, C.[Claudio], Seidenari, L.[Lorenzo], del Bimbo, A.[Alberto],
Segmentation Free Object Discovery in Video,
MotionRep16(III: 25-31).
Springer DOI 1611
BibRef

Li, X.D.[Xu-Dong], Ye, M.[Mao], Liu, Y.G.[Yi-Guang], Zhang, F.[Feng], Liu, D.[Dan], Tang, S.[Song],
Accurate object detection using memory-based models in surveillance scenes,
PR(67), No. 1, 2017, pp. 73-84.
Elsevier DOI 1704
Convolutional neural network 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

Tu, Z.G.[Zhi-Gang], Guo, Z.[Zuwei], Xie, W.[Wei], Yan, M.[Mengjia], Veltkamp, R.C.[Remco C.], Li, B.X.[Bao-Xin], Yuan, J.S.[Jun-Song],
Fusing disparate object signatures for salient object detection in video,
PR(72), No. 1, 2017, pp. 285-299.
Elsevier DOI 1708
Spatiotemporal saliency computation BibRef

Koh, Y.J., Kim, C.S.,
Unsupervised Primary Object Discovery in Videos Based on Evolutionary Primary Object Modeling With Reliable Object Proposals,
IP(26), No. 11, November 2017, pp. 5203-5216.
IEEE DOI 1709
image sequences, object detection, video signal processing, POD algorithm, evolutionary primary object modeling technique, foreground confidence, motion-based object proposals, random walk, recurrence property, reliable object proposals, temporal correlations, unsupervised primary object discovery algorithm, Motion segmentation, Proposals, Reliability, Spatiotemporal phenomena, Trajectory, Primary object discovery, recurrence property, BibRef

Koh, Y.J., Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
POD: Discovering Primary Objects in Videos Based on Evolutionary Refinement of Object Recurrence, Background, and Primary Object Models,
CVPR16(1068-1076)
IEEE DOI 1612
BibRef

Jang, W.D.[Won-Dong], Lee, C., Kim, C.S.[Chang-Su],
Primary Object Segmentation in Videos via Alternate Convex Optimization of Foreground and Background Distributions,
CVPR16(696-704)
IEEE DOI 1612
BibRef

Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Streaming Video Segmentation via Short-Term Hierarchical Segmentation and Frame-by-Frame Markov Random Field Optimization,
ECCV16(VI: 599-615).
Springer DOI 1611
BibRef

Spampinato, C.[Concetto], Palazzo, S.[Simone], Giordano, D.[Daniela],
Gamifying Video Object Segmentation,
PAMI(39), No. 10, October 2017, pp. 1942-1958.
IEEE DOI 1709
BibRef
Earlier: A1, A2, Only:
Enhancing object detection performance by integrating motion objectness and perceptual organization,
ICPR12(3640-3643).
WWW Link. 1302
is the blob an object of interest.. Data mining, Games, Motion segmentation, Object segmentation, Visualization, Interactive video annotation, games with a purpose, human in the loop, spatio-temporal, superpixel segmentation BibRef

Giordano, D.[Daniela], Kavasidis, I.[Isaak], Palazzo, S.[Simone], Spampinato, C.[Concetto],
Rejecting False Positives in Video Object Segmentation,
CAIP15(I:100-112).
Springer DOI 1511
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


Xiao, B.[Bo], Wang, B.[Bin],
Efficient HD video and image salient object detection with hierarchical boolean map approach,
ICIVC17(1-7)
IEEE DOI 1708
Acceleration, Algorithm design and analysis, Feature extraction, Floods, Image resolution, Object detection, Visualization, hierarchical boolean map, parallel processing, salient object detection, video consistency BibRef

Yang, Y.C.[Ying-Chun], Peng, Y.C.[Yu-Chen], Han, S.D.[Shou-Dong],
Video segmentation based on patch matching and enhanced Onecut,
ICIVC17(346-350)
IEEE DOI 1708
Color, Image color analysis, Image edge detection, Optical imaging, Optical noise, Optical sensors, Shape, enhanced onecut, local classifier, patch matching, video, segmentation BibRef

Zhang, L.[Long], Liu, Y.J.[Yu-Jun], Han, S.D.[Shou-Dong],
Video segmentation based on strong target constrained video saliency,
ICIVC17(356-360)
IEEE DOI 1708
Adaptive optics, Image color analysis, Image segmentation, Optical imaging, Robustness, Target tracking, full-connected conditional random field, object proposal, super-pixel, video saliency, video, segmentation BibRef

Chan, K.L.,
Saliency/non-saliency segregation in video sequences using perception-based local ternary pattern features,
MVA17(510-513)
DOI Link 1708
Adaptation models, Color, Computational modeling, History, Image color analysis, Mathematical model, Video sequences 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, Computer vision, Histograms, Image motion analysis, Motion segmentation, Optical, imaging BibRef

Masuda, M., Mochizuki, Y., Ishikawa, H.,
Unsupervised video object segmentation by supertrajectory labeling,
MVA17(448-451)
DOI Link 1708
Color, Labeling, Motion segmentation, Object segmentation, Optimization, Robustness, Trajectory 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

Sun, L.[Lu], Décombas, M.[Marc], Lang, J.[Jochen],
Video Object Segmentation for Content-Aware Video Compression,
CRV16(116-123)
IEEE DOI 1612
BibRef

Tsai, Y.H.[Yi-Hsuan], Yang, M.H.[Ming-Hsuan], Black, M.J.[Michael J.],
Video Segmentation via Object Flow,
CVPR16(3899-3908)
IEEE DOI 1612
BibRef

Kundu, A.[Abhijit], Vineet, V.[Vibhav], Koltun, V.[Vladlen],
Feature Space Optimization for Semantic Video Segmentation,
CVPR16(3168-3175)
IEEE DOI 1612
BibRef

Lu, Y.[Yao], Bai, X.[Xue], Shapiro, L.G.[Linda G.], Wang, J.[Jue],
Coherent Parametric Contours for Interactive Video Object Segmentation,
CVPR16(642-650)
IEEE DOI 1612
BibRef

Janus, P.[Piotr], Piszczek, K.[Kamil], Kryjak, T.[Tomasz],
FPGA Implementation of the Flux Tensor Moving Object Detection Method,
ICCVG16(486-497).
Springer DOI 1611
BibRef

Hur, J.[Junhwa], Roth, S.[Stefan],
Joint Optical Flow and Temporally Consistent Semantic Segmentation,
CVRoads16(I: 163-177).
Springer DOI 1611
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

Bhatti, A.H., Rahman, A., Butt, A.A.,
Video segmentation using spectral clustering on superpixels,
ICIP16(869-873)
IEEE DOI 1610
Color BibRef

Martins, I.[Isabel], Carvalho, P.[Pedro], Corte-Real, L.[Luís], Alba-Castro, J.L.[José Luis],
Bio-inspired Boosting for Moving Objects Segmentation,
ICIAR16(397-406).
Springer DOI 1608
BibRef

Le, T.N.[Trung-Nghia], Sugimoto, A.[Akihiro],
Contrast Based Hierarchical Spatial-Temporal Saliency for Video,
PSIVT15(734-748).
Springer DOI 1602
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

Xue, K.[Kang], Wang, X.[Xiying], Ma, G.Y.[Geng-Yu], Wang, H.T.[Hai-Tao], Nam, D.[Dong_Kyung],
A video saliency detection method based on spatial and motion information,
ICIP15(412-416)
IEEE DOI 1512
Classification; Motion; Saliency; Video BibRef

Bosch, M.[Marc], Li, G.[Guiqin], Wang, K.[Kai],
A two-stage video object segmentation using motion and color information,
ICIP15(3916-3920)
IEEE DOI 1512
object segmentation; video segmentation; video summary 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

Wu, Z.Y.[Zheng-Yang], Li, F.[Fuxin], Sukthankar, R.[Rahul], Rehg, J.M.[James M.],
Robust video segment proposals with painless occlusion handling,
CVPR15(4194-4203)
IEEE DOI 1510
BibRef

Fragkiadaki, K.[Katerina], Arbelaez, P.[Pablo], Felsen, P.[Panna], Malik, J.[Jitendra],
Learning to segment moving objects in videos,
CVPR15(4083-4090)
IEEE DOI 1510
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

Misra, I.[Ishan], Shrivastava, A.[Abhinav], Hebert, M.[Martial],
Watch and learn: Semi-supervised learning of object detectors from videos,
CVPR15(3593-3602)
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.[Nick], 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.[Dongdong], 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

Mukherjee, D.[Dibyendu], Wu, Q.M.J.[Q.M. Jonathan],
Streaming spatio-temporal video segmentation using Gaussian Mixture Model,
ICIP14(4388-4392)
IEEE DOI 1502
Clustering algorithms BibRef

Weber, M.[Markus], Liwicki, M.[Marcus], Stricker, D.[Didier], Scholzel, C.[Christopher], Uchida, S.[Seiichi],
LSTM-Based Early Recognition of Motion Patterns,
ICPR14(3552-3557)
IEEE DOI 1412
LSTM: Long Short-Term Memory. Accuracy 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
BibRef

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
BibRef

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
BibRef

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).
HTML Version. 1410
Video segmentation. BibRef

Teney, D.[Damien], Hebert, M.[Martial],
Learning to Extract Motion from Videos in Convolutional Neural Networks,
ACCV16(V: 412-428).
Springer DOI 1704
BibRef

Teney, D.[Damien], Brown, M.[Matthew], Kit, D.[Dimitry], Hall, P.[Peter],
Learning similarity metrics for dynamic scene segmentation,
CVPR15(2084-2093)
IEEE DOI 1510
BibRef

Teney, D.[Damien], Brown, M.[Matthew],
Segmentation of Dynamic Scenes with Distributions of Spatiotemporally Oriented Energies,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Faktor, A.[Alon], Irani, M.[Michal],
Video Segmentation by Non-Local Consensus voting,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Morimitsu, H.[Henrique], Cesar, Jr., R.M.[Roberto M.], Bloch, I.[Isabelle],
A Spatio-temporal Approach for Multiple Object Detection in Videos Using Graphs and Probability Maps,
ICIAR14(II: 421-428).
Springer DOI 1410
BibRef

Jung, H.[Heechul], Ju, J.[Jeongwoo], Kim, J.[Junmo],
Rigid Motion Segmentation Using Randomized Voting,
CVPR14(1210-1217)
IEEE DOI 1409
motion segmentation; multiview; randomized voting; rigid motion; two view BibRef

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

Oneata, D.[Dan], Revaud, J.[Jerome], Verbeek, J.[Jakob], Schmid, C.[Cordelia],
Spatio-temporal Object Detection Proposals,
ECCV14(III: 737-752).
Springer DOI 1408
The bounding boxes to use in event detection. See also Action and Event Recognition with Fisher Vectors on a Compact Feature Set. BibRef

Hiratani, A., Nakashima, R., Matsumiya, K., Kuriki, I., Shioiri, S.,
Considerations of Self-Motion in Motion Saliency,
ACPR13(783-787)
IEEE DOI 1408
feature extraction BibRef

Agarwal, D., Soni, N., Namboodiri, A.M.,
Salient object detection in SfM point cloud,
NCVPRIPG13(1-4)
IEEE DOI 1408
image motion analysis BibRef

Ortega, M.,
Hook: Heuristics for selecting 3D moving objects in dense target environments,
3DUI13(119-122)
IEEE DOI 1406
interactive systems BibRef

Gan, C.[Chuang], Qin, Z.C.[Zeng-Chang], Xu, J.[Jia], Wan, T.[Tao],
Salient object detection in image sequences via spatial-temporal cue,
VCIP13(1-6)
IEEE DOI 1402
feature extraction BibRef

Jain, A.[Aastha], Chatterjee, S.[Shuanak], Vidal, R.[Rene],
Coarse-to-Fine Semantic Video Segmentation Using Supervoxel Trees,
ICCV13(1865-1872)
IEEE DOI 1403
Image segmentation 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], Protzel, P.[Peter],
Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Couprie, C.[Camille], Farabet, C.[Clement], le Cun, Y.[Yann], Najman, L.[Laurent],
Causal graph-based video segmentation,
ICIP13(4249-4253)
IEEE DOI 1402
Optimization; graph-matching; superpixels BibRef

Pu, S.T.[Song-Tao], Zha, H.B.[Hong-Bin],
Streaming video object segmentation with the adaptive coherence factor,
ICIP13(4235-4238)
IEEE DOI 1402
Video object segmentation BibRef

Nawaf, M.M.[Mohamad Motasem], Hasnat, M.A.[M. Abul], Sidibe, D.[Desire], Tremeau, A.[Alain],
Color and flow based superpixels for 3D geometry respecting meshing,
WACV14(153-158)
IEEE DOI 1406
Adaptive optics BibRef

Muddamsetty, S.M.[Satya M.], Sidibe, D.[Desire], Tremeau, A.[Alain], Meriaudeau, F.[Fabrice],
Spatio-temporal Saliency Detection in Dynamic Scenes Using Local Binary Patterns,
ICPR14(2353-2358)
IEEE DOI 1412
BibRef
Earlier:
A performance evaluation of fusion techniques for spatio-temporal saliency detection in dynamic scenes,
ICIP13(3924-3928)
IEEE DOI 1402
Computational modeling. Spatio-temporal saliency BibRef

Meuel, H.[Holger], Reso, M.[Matthias], Jachalsky, J.[Jorn], Ostermann, J.[Jorn],
Superpixel-based segmentation of moving objects for low bitrate ROI coding systems,
AVSS13(395-400)
IEEE DOI 1311
Bandwidth BibRef

Feng, W.G.[Wei-Guo], Liu, R.[Rui], Jia, B.[Baozhi], 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
BibRef

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
BibRef

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

Zhang, D.[Dong], Javed, O.[Omar], Shah, M.[Mubarak],
Video Object Co-segmentation by Regulated Maximum Weight Cliques,
ECCV14(VII: 551-566).
Springer DOI 1408
BibRef
Earlier:
Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions,
CVPR13(628-635)
IEEE DOI 1309
Computer Vision; Object Segmentation; Video Segmentation BibRef

Xiang, X.[Xiang], Chang, H.[Hong], Luo, J.B.[Jie-Bo],
Online Web-Data-Driven Segmentation of Selected Moving Objects in Videos,
ACCV12(II:134-146).
Springer DOI 1304
BibRef

Ellis, L.[Liam], Zografos, V.[Vasileios],
Online Learning for Fast Segmentation of Moving Objects,
ACCV12(II:52-65).
Springer DOI 1304
BibRef

Di, X.F.[Xiao-Fei], Chang, H.[Hong], Chen, X.L.[Xi-Lin],
Multi-layer Spectral Clustering for Video Segmentation,
ACCV12(II:1-12).
Springer DOI 1304
BibRef

Xiong, H.[Hao], Wang, Z.Y.[Zhi-Yong], He, R.J.[Ren-Jie], Feng, D.D.,
Video Object Segmentation with Occlusion Map,
DICTA12(1-7).
IEEE DOI 1303
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
BibRef

Xie, D.F.[Dan-Feng], Huang, Z.W.[Zhi-Wei], Wang, S.Z.[Shi-Zheng], Liu, H.G.[He-Guang],
Moving Objects Segmentation from compressed surveillance video based on Motion Estimation,
ICPR12(3132-3135).
WWW Link. 1302
BibRef

Ji, H.[Hao], Su, F.[Fei],
Robust motion segmentation via refined sparse subspace clustering,
ICPR12(1546-1549).
WWW Link. 1302
BibRef

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
BibRef

Yang, J.W.[Jian-Wei], Wang, S.Z.[Shi-Zheng], Lei, Z.[Zhen], Zhao, Y.Y.[Yan-Yun], Li, S.Z.[Stan Z.],
Spatio-temporal LBP Based Moving Object Segmentation in Compressed Domain,
AVSS12(252-257).
IEEE DOI 1211
BibRef

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
BibRef

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:
WWW Link. BibRef

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
BibRef

Cheng, H.T.T.[Hsien-Ting Tim], Ahuja, N.[Narendra],
Exploiting nonlocal spatiotemporal structure for video segmentation,
CVPR12(741-748).
IEEE DOI 1208
BibRef

Ma, T.Y.[Tian-Yang], Latecki, L.J.[Longin Jan],
Maximum weight cliques with mutex constraints for video object segmentation,
CVPR12(670-677).
IEEE DOI 1208
BibRef

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

Ye, Y.[Yun], Ci, S.[Song], Liu, Y.W.[Yan-Wei], Tang, H.[Hui],
Dynamic video object detection with single PTU camera,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Wang, Y.Y.[Yi-Ying], Lee, C.H.[Chia-Han],
Segmentation by temporal detection integration,
ICIP11(3125-3128).
IEEE DOI 1201
BibRef

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
BibRef

Hui, Z.[Zhao], Xiangju, S.[Sun], Caihong, M.[Meng],
Moving object detection based on T-test combined with kirsch operator,
IASP11(199-203).
IEEE DOI 1112
BibRef

Lalos, C.[Constantinos], Grabner, H.[Helmut], Van Gool, L.J.[Luc J.], Varvarigou, T.A.[Theodora A.],
Object Flow: Learning Object Displacement,
VS10(133-142).
Springer DOI 1109
BibRef

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
BibRef

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
BibRef

Zografos, V.[Vasileios],
Enhancing motion segmentation by combination of complementary affinities,
ICPR12(2198-2201).
WWW Link. 1302
BibRef

Zografos, V.[Vasileios], Nordberg, K.[Klas],
Fast and accurate motion segmentation using Linear Combination of Views,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Zografos, V.[Vasileios], Nordberg, K.[Klas], Ellis, L.[Liam],
Sparse Motion Segmentation Using Multiple Six-Point Consistencies,
VECTaR10(338-348).
Springer DOI 1109
BibRef

Nordberg, K.[Klas], Zografos, V.[Vasileios],
Multibody Motion Segmentation Using the Geometry of 6 Points in 2D Images,
ICPR10(1783-1787).
IEEE DOI 1008
BibRef

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
BibRef

Gao, P.[Ping], Sun, X.J.[Xiang-Ju], Wang, W.[Wei],
Moving object detection based on Kirsch operator combined with Optical Flow,
IASP10(620-624).
IEEE DOI 1004
BibRef

van Essen, G., Marsland, S., Lewis, J.,
Hierarchical block-based image registration for computing multiple image motions,
IVCNZ09(425-430).
IEEE DOI 0911
BibRef

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
BibRef

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
BibRef

Wang, Y.N.[Yan-Ni], Fan, Y.Y.[Yang-Yu],
Adaptive Motion Segmentation Based on Genetic Algorithm,
CISP09(1-4).
IEEE DOI 0910
BibRef

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
BibRef

Fraile, R.[Roberto], Hogg, D.C.[David C.], Cohn, A.G.[Anthony G.],
Motion segmentation by consensus,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Li, H.W.[Hong-Wei], Lin, L.[Liang], Wu, T.F.[Tian-Fu], Liu, X.B.[Xiao-Bai], Dong, L.F.[Lan-Fang],
Object-of-interest extraction by integrating stochastic inference with learnt active shape sketch,
ICPR08(1-4).
IEEE DOI 0812
BibRef

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
BibRef

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
BibRef

García, A.[Alvaro], Bescós, J.[Jesús],
Video Object Segmentation Based on Feedback Schemes Guided by a Low-Level Scene Ontology,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef

Langs, G.[Georg], Paragios, N.[Nikos],
Modeling the structure of multivariate manifolds: Shape maps,
CVPR08(1-8).
IEEE DOI 0806
BibRef

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).
PDF File. 0709
BibRef

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
BibRef

Qin, X.K.[Xiao-Ke], Tang, L.[Liang], Zhou, J.[Jie],
Object Extraction by Spatio-Temporal Assembling,
ICIP07(V: 153-156).
IEEE DOI 0709
BibRef

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

Galmar, E.[Eric], Huet, B.[Benoit],
Graph-Based Spatio-temporal Region Extraction,
ICIAR06(I: 236-247).
Springer DOI 0610
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

Al-Mazeed, A.[Ahmad], Nixon, M.S.[Mark S.], Gunn, S.R.[Steve R.],
Classifiers Combination for Improved Motion Segmentation,
ICIAR04(II: 363-371).
Springer DOI 0409
BibRef

Barbu, A.[Adrian], Zhu, S.C.[Song Chun],
On the Relationship Between Image and Motion Segmentation,
SCVMA04(51-63).
Springer DOI 0405
BibRef

Kahl, F.[Fredrik], Hartley, R.I.[Richard I.], Hilsenstein, V.[Volker],
Novelty Detection in Image Sequences with Dynamic Background,
SMVP04(117-128).
Springer DOI 0505
BibRef

Kaempchen, N.[Nico], Zocholl, M.[Markus], Dietmayer, K.C.J.[Klaus C.J.],
Spatio-temporal Segmentation Using Laser-scanner and Video Sequences,
DAGM04(367-374).
Springer DOI 0505
BibRef

Wildenauer, H.[Horst], Blauensteiner, P.[Philipp], Hanbury, A.[Allan], Kampel, M.[Martin],
Motion Detection Using an Improved Colour Model,
ISVC06(II: 607-616).
Springer DOI 0611
BibRef

Mármol, S.B.L.[Salvador B. López], Artner, N.M.[Nicole M.], Ion, A.[Adrian], Kropatsch, W.G.[Walter G.], Beleznai, C.[Csaba],
Video Object Segmentation Using Graphs,
CIARP08(733-740).
Springer DOI 0809
BibRef

Marchadier, J.[Jocelyn], Kropatsch, W.G.[Walter G.], Hanbury, A.[Allan],
The Redundancy Pyramid and Its Application to Segmentation on an Image Sequence,
DAGM04(432-439).
Springer DOI 0505
BibRef

Chen, M.L.[Mao-Lin], Ma, G.Y.[Geng-Yu], Kee, S.C.[Seok-Cheol],
Pixels Classification for Moving Object Extraction,
Motion05(II: 44-49).
IEEE DOI 0502
BibRef

Myerscough, P.J., Nixon, M.S.,
Estimating the phase congruency of localised frequencies,
ICIP04(I: 275-278).
IEEE DOI 0505
BibRef
And:
Temporal phase congruency,
Southwest04(76-79).
WWW Link. 0411
Moving feature detector. BibRef

Tweed, D.,
Estimating rigid motions via the conformal model of Euclidean space,
ICPR04(II: 171-174).
IEEE DOI 0409
BibRef

Nair, V., Clark, J.J.,
An unsupervised, online learning framework for moving object detection,
CVPR04(II: 317-324).
IEEE DOI 0408
BibRef

Toth, D., Aach, T.,
Detection and recognition of moving objects using statistical motion detection and Fourier descriptors,
CIAP03(430-435).
IEEE DOI 0310
BibRef

Kim, D.H.[Dae-Hee], Ahn, C.H.[Chung-Hyun], No, Y.S.[Yo-Sung],
Video segmentation using vector-valued diffusion and clustering,
ICIP03(I: 989-992).
IEEE DOI 0312
BibRef

Rousson, M., Deriche, R.,
A variational framework for active and adaptative segmentation of vector valued images,
Motion02(56-61).
IEEE DOI 0303
BibRef

Porikli, F.M.[Fatih Murat],
Object Segmentation of Color Video Sequences,
CAIP01(610 ff.).
Springer DOI 0210
BibRef

Porikli, F.M., Wang, Y.,
An Unsupervised Multi-resolution Object Extraction Algorithm Using Video-cube,
ICIP01(II: 359-362).
IEEE DOI 0108
BibRef

Yoshida, T., Shimosato, T.,
Motion Image Segmentation Using 3-d Watershed Algorithm,
ICIP01(II: 773-776).
IEEE DOI 0108
BibRef

Yamada, A.[Akio], Ohta, M.[Mutsumi],
A Study of Region Partitioning Using Reciprocal Estimation of Region Models and Pixel Motion,
ICIP99(I:1-5).
IEEE DOI BibRef 9900

Kim, C.I.[Changick I.], Hwang, J.N.[Jenq-Neng],
A Fast and Robust Moving Object Segmentation in Video Sequences,
ICIP99(II:131-134).
IEEE DOI BibRef 9900

Murphey, Y.L., Lu, H., Lakshmanan, S., Karlsen, R.E., Gerhart, G.R., Meitzler, T.J.,
Dyta: an intelligent system for moving target detection,
CIAP99(1116-1121).
IEEE DOI 9909
BibRef

de Smet, P., and de Vleeschauwer, D.,
Motion-Based Segmentation Using a Thresholded Merging Strategy on Watershed Segments,
ICIP97(II: 490-493).
IEEE DOI BibRef 9700

Csillag, P., and Boroczky, L.,
Iterative Motion-Based Segmentation for Object-Based Video Coding,
ICIP97(I: 73-76).
IEEE DOI BibRef 9700

Yip, H.M.[Hoi-Man], Pong, T.C.[Ting-Chuen],
Detection of moving objects using a spatiotemporal representation,
ICPR96(I: 483-487).
IEEE DOI 9608
(The Hong Kong Univ., HK) BibRef

Hoetter, M., Mester, R., Meyer, M.,
Detection of Moving Objects Using a Robust Displacement Estimation Including a Statistical Error Analysis,
ICPR96(IV: 249-255).
IEEE DOI 9608
(Robert Bosch GmbH, D) BibRef

James, P.D., Spann, M.,
Multiresolution Motion Estimation/Segmentation Incorporating Feature Correspondence and Optical Flow,
BMVC95(xx-yy).
PDF File. 9509
BibRef

Xiong, W.[Wei], Graffigne, C.,
A hierarchical method for detection of moving objects,
ICIP94(II: 795-799).
IEEE DOI 9411
BibRef

Cloutier, L., Mitiche, A., Bouthemy, P.,
Segmentation and estimation of image motion by a robust method,
ICIP94(II: 805-809).
IEEE DOI 9411
BibRef

Ayer, S., Schroeter, P., Bigün, J.,
Segmentation of Moving Objects by Robust Motion Parameter Estimation over Multiple Frames,
ECCV94(B:316-327).
Springer DOI BibRef 9400

Ayer, S.[Serge],
Sequential and Competitive Methods for the Estimation of Multiple Motions,
Ph.D.Thesis, EPFL, Lausanne, 1995. BibRef 9500

Hirai, T., Sasakawa, K., Kuroda, S., Ikebata, S.,
Detection of small moving object by optical flow,
ICPR92(II:474-478).
IEEE DOI 9208
BibRef

Anbalagan, R.S., Hu, G., Jain, A.K.,
A segmentation and object extraction algorithm with linear memory and time constraints,
ICPR88(I: 596-600).
IEEE DOI 8811
BibRef

Darmon, C.A.,
A New Recursive Method to Detect Moving Objects in a Sequence of Images,
PRIP82(259-261). BibRef 8200

Bers, K.H., Bohner, M., Gerlach, H.,
Object Detection in Image Sequences,
ICPR80(1317-1319). BibRef 8000

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Motion Segmentation by Tracking, Trajectories, Region Based Tracking .


Last update:Nov 11, 2017 at 13:31:57