18.3.4 Extract Moving Objects from Image Sequences or Video

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

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

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

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

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

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

Li, X.[Xi], Ning, Z.N.[Zheng-Nan], Xiang, L.W.[Liu-Wei],
Robust Multi-Body Motion Segmentation Based on Fuzzy k-Subspace Clustering,
IEICE(E88-D), No. 11, November 2005, pp. 2609-2614.
DOI Link 0511
See also Robust 3D Reconstruction with Outliers Using RANSAC Based Singular Value Decomposition. BibRef

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

Garcia, V.[Vincent], Boltz, S.[Sylvain], Debreuve, E.[Eric], Barlaud, M.[Michel],
Outer-Layer Based Tracking using Entropy as a Similarity Measure,
ICIP07(VI: 309-312).
IEEE DOI 0709
See also Using the Shape Gradient for Active Contour Segmentation: From the Continuous to the Discrete Formulation. BibRef

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Bansal, V.[Vaibhav], James, S.[Stuart], del Bue, A.[Alessio],
re-OBJ: Jointly Learning the Foreground and Background for Object Instance Re-identification,
CIAP19(II:402-413).
Springer DOI 1909
BibRef

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

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

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

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

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

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

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

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

Chen, Y.[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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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
BibRef
And:
Primary Object Segmentation in Videos Based on Region Augmentation and Reduction,
CVPR17(7417-7425)
IEEE DOI 1711
Color, Motion segmentation, Object segmentation, Proposals, Target tracking, Video sequences, Videos. POD algorithm, evolutionary primary object modeling technique, foreground confidence, motion-based object proposals, BibRef

Koh, Y.J., Kim, C.S.,
CDTS: Collaborative Detection, Tracking, and Segmentation for Online Multiple Object Segmentation in Videos,
ICCV17(3621-3629)
IEEE DOI 1802
image segmentation, image sequences, object detection, object tracking, video signal processing, CDTS, Videos BibRef

Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Semi-supervised Video Object Segmentation Using Multiple Random Walkers,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Koh, Y.J.[Yeong Jun], Lee, Y.Y.[Young-Yoon], Kim, C.S.[Chang-Su],
Sequential Clique Optimization for Video Object Segmentation,
ECCV18(XIV: 537-556).
Springer DOI 1810
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], Kim, C.S.[Chang-Su],
Online Video Object Segmentation via Convolutional Trident Network,
CVPR17(7474-7483)
IEEE DOI 1711
Decoding, Feature extraction, Image segmentation, Motion segmentation, Object segmentation, Streaming media, Target, tracking BibRef

Lee, S.H., Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Contour-Constrained Superpixels for Image and Video Processing,
CVPR17(5863-5871)
IEEE DOI 1711
Cost function, Image color analysis, Image segmentation, Labeling, Linear programming, Pattern, matching 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

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

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

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

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

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

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

Gangapure, V.N.[Vijay N.], Nanda, S.[Susmit], Chowdhury, A.S.[Ananda S.], Jiang, X.Y.[Xiao-Yi],
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Object segmentation, Noise measurement, Proposals, Markov random fields, Task analysis, Probabilistic logic, probabilistic graphical model BibRef

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IEEE DOI 1904
Object detection, Robustness, Sparse matrices, Video surveillance, Video sequences, Context modeling, Big data, mutiple scenarios, moving object detection BibRef

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IEEE DOI 1908
image motion analysis, image resolution, image segmentation, optimisation, video signal processing, appearance, motion clues, semantic classification BibRef

Gu, S.[Song], Wang, J.[Jian], Du, Y.J.[Ying-Jie], Zhang, W.R.[Wei-Rui], Hao, W.[Wei], Zhou, D.M.[Dong-Mei],
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IVC(88), 2019, pp. 19-28.
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IEEE DOI 1910
image denoising, image fusion, image motion analysis, image segmentation, object detection, unsupervised learning, video understanding BibRef

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Object detection in videos, object linking BibRef

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Videos, Ice, Object segmentation, Encoding, Motion segmentation, Trajectory, Decoding, Video object segmentation, interactively constrained encoding BibRef

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WACV20(1979-1988)
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Heuristic algorithms, Vehicle dynamics, Videos, Feature extraction, Cameras, Task analysis, Dynamics BibRef

Sun, M.J.[Ming-Jie], Xiao, J.M.[Ji-Min], Lim, E.G.[Eng Gee], Xie, Y.C.[Yan-Chun], Feng, J.S.[Jia-Shi],
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IEEE DOI 2007
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IEEE DOI 1812
Motion segmentation, Active contours, Optical imaging, Image segmentation, Optical propagation, Task analysis, spatial-temporal embedding. Image segmentation, Optical sensors, Level set, Object segmentation BibRef


Chen, Y., Cao, Y., Hu, H., Wang, L.,
Memory Enhanced Global-Local Aggregation for Video Object Detection,
CVPR20(10334-10343)
IEEE DOI 2008
Semantics, Object detection, Feature extraction, Detectors, Aggregates, Object recognition, Optical imaging BibRef

Yin, J., Shen, J., Guan, C., Zhou, D., Yang, R.,
LiDAR-Based Online 3D Video Object Detection With Graph-Based Message Passing and Spatiotemporal Transformer Attention,
CVPR20(11492-11501)
IEEE DOI 2008
Feature extraction, Spatiotemporal phenomena, Detectors, Object detection, Encoding, Message passing BibRef

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

Zhang, Y., Wu, Z., Peng, H., Lin, S.,
A Transductive Approach for Video Object Segmentation,
CVPR20(6947-6956)
IEEE DOI 2008
Object segmentation, Task analysis, Video sequences, Computational modeling, History, Estimation, Data models BibRef

Patil, P.W., Biradar, K.M., Dudhane, A., Murala, S.,
An End-to-End Edge Aggregation Network for Moving Object Segmentation,
CVPR20(8146-8155)
IEEE DOI 2008
Videos, Feature extraction, Decoding, Object segmentation, Optical imaging, Task analysis, Visualization BibRef

Huang, X.H.[Xu-Hua], Xu, J.R.[Jia-Rui], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching,
CVPR20(8876-8886)
IEEE DOI 2008
Object segmentation, Pipelines, Benchmark testing, Semantics, Image segmentation, Task analysis, Feature extraction BibRef

Lu, X., Wang, W., Shen, J., Tai, Y., Crandall, D.J., Hoi, S.C.H.,
Learning Video Object Segmentation From Unlabeled Videos,
CVPR20(8957-8967)
IEEE DOI 2008
Semantics, Supervised learning, Visualization, Training, Data models, Object segmentation, Machine learning BibRef

Chen, X., Li, Z., Yuan, Y., Yu, G., Shen, J., Qi, D.,
State-Aware Tracker for Real-Time Video Object Segmentation,
CVPR20(9381-9390)
IEEE DOI 2008
Target tracking, Robustness, Task analysis, Pipelines, Object segmentation, State estimation, Video sequences BibRef

Hu, P., Caba, F., Wang, O., Lin, Z., Sclaroff, S., Perazzi, F.,
Temporally Distributed Networks for Fast Video Semantic Segmentation,
CVPR20(8815-8824)
IEEE DOI 2008
Feature extraction, Computational modeling, Image segmentation, Semantics, Aggregates, Encoding, Task analysis BibRef

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

Luiten, J., Zulfikar, I.E., Leibe, B.,
UnOVOST: Unsupervised Offline Video Object Segmentation and Tracking,
WACV20(1989-1998)
IEEE DOI 2006
Task analysis, Proposals, Object segmentation, Forestry, Motion segmentation, Visualization, Tracking BibRef

Qian, Y., Yu, L., Liu, W., Kang, G., Hauptmann, A.G.,
Adaptive Feature Aggregation for Video Object Detection,
WACVWS20(143-147)
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Feature extraction, Adaptation models, Object detection, Task analysis, Context modeling, Rats BibRef

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

Mustafa, A., Russell, C., Hilton, A.,
U4D: Unsupervised 4D Dynamic Scene Understanding,
ICCV19(10422-10431)
IEEE DOI 2004
image motion analysis, image reconstruction, image segmentation, image sequences, object detection, pose estimation, Estimation BibRef

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

Arrigoni, F., Pajdla, T.,
Robust Motion Segmentation From Pairwise Matches,
ICCV19(671-681)
IEEE DOI 2004
image matching, image motion analysis, image segmentation, pairwise matches, Structure from motion BibRef

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

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

Bujanca, M., Lujan, M., Lennox, B.,
FullFusion: A Framework for Semantic Reconstruction of Dynamic Scenes,
3D-Wild19(2168-2177)
IEEE DOI 2004
image colour analysis, image motion analysis, image reconstruction, image segmentation, mobile robots, dynamic SLAM BibRef

Guo, C., Fan, B., Gu, J., Zhang, Q., Xiang, S., Prinet, V., Pan, C.,
Progressive Sparse Local Attention for Video Object Detection,
ICCV19(3908-3917)
IEEE DOI 2004
feature extraction, image representation, image sequences, object detection, video signal processing, Optical detectors BibRef

Yang, Z.[Zhao], Wang, Q.[Qiang], Bertinetto, L.[Luca], Bai, S.[Song], Hu, W.[Weiming], Torr, P.H.S.[Philip H.S.],
Anchor Diffusion for Unsupervised Video Object Segmentation,
ICCV19(931-940)
IEEE DOI 2004
image segmentation, image sequences, learning (artificial intelligence), object detection, Task analysis BibRef

Wang, Q.[Qiang], He, Y.[Yi], Yang, X.Y.[Xiao-Yun], Yang, Z.[Zhao], Torr, P.H.S.[Philip H.S.],
An Empirical Study of Detection-Based Video Instance Segmentation,
YouTube-VOS19(713-716)
IEEE DOI 2004
image segmentation, object detection, object tracking, video signal processing, siamese tracker BibRef

Mao, H., Yang, X., Dally, B.,
A Delay Metric for Video Object Detection: What Average Precision Fails to Tell,
ICCV19(573-582)
IEEE DOI 2004
object detection, video signal processing, video object detector, video object detection methods, delay metric, average precision, Task analysis BibRef

Deng, J., Pan, Y., Yao, T., Zhou, W., Li, H., Mei, T.,
Relation Distillation Networks for Video Object Detection,
ICCV19(7022-7031)
IEEE DOI 2004
feature extraction, image classification, object detection, video signal processing, video object detection, Aggregates BibRef

Shvets, M., Liu, W., Berg, A.,
Leveraging Long-Range Temporal Relationships Between Proposals for Video Object Detection,
ICCV19(9755-9763)
IEEE DOI 2004
object detection, pose estimation, video signal processing, long-range temporal dependencies, temporal relation module, Indexes BibRef

Zolfaghari Bengar, J., Gonzalez-Garcia, A., Villalonga, G., Raducanu, B., Habibi Aghdam, H., Mozerov, M., Lopez, A.M., van de Weijer, J.,
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ICCV19(8479-8488)
IEEE DOI 2004
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Oh, S.W., Lee, J., Xu, N., Kim, S.J.,
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ICCV19(9225-9234)
IEEE DOI 2004
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Yang, Z., Li, P., Feng, Q., Wei, Y., Yang, Y.,
Going Deeper Into Embedding Learning for Video Object Segmentation,
YouTube-VOS19(697-700)
IEEE DOI 2004
image motion analysis, image segmentation, learning (artificial intelligence), object detection, object recognition BibRef

Luiten, J., Voigtlaender, P., Leibe, B.,
Exploring the Combination of PReMVOS, BoLTVOS and UnOVOST for the 2019 YouTube-VOS Challenge,
YouTube-VOS19(705-708)
IEEE DOI 2004
image segmentation, object detection, object tracking, video signal processing, UnOVOST, segmentation BibRef

Zhang, X.[Xuan], Han, G.X.[Guang-Xing], He, W.D.[Wen-Duo],
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IEEE DOI 2002
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IEEE DOI 2002
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IEEE DOI 2002
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IEEE DOI 2002
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IEEE DOI 2002
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Roshan, A., Zhang, Y.,
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Adversarial attacks, black / gray-box, non-gradient / gradient based attacks, defense, machine learning BibRef

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ICIP19(2015-2019)
IEEE DOI 1910
Anomaly Detection, Optical Flow BibRef

Zhang, C., Kim, J.,
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ICIP19(71-75)
IEEE DOI 1910
Video object detection, deep learning, optical flow, LSTM, context modeling BibRef

Duque-Arias, D., Velasco-Forero, S., Deschaud, J.E., Goulette, F., Marcotegui, B.,
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Video Object Segmentation with Language Referring Expressions,
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Springer DOI 1906
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Xie, R.J.[Ren-Jie], Wang, Y.C.[Yuan-Cheng], Xie, T.[Tian], Zhang, Y.H.[Yu-Hao], Xu, L.[Li], Lu, J.[Jian], Wang, Q.[Qiao],
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CVPR18(7210-7218)
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Chandra, S., Couprie, C., Kokkinos, I.[Iasonas],
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation,
CVPR18(8915-8924)
IEEE DOI 1812
Image segmentation, Semantics, Task analysis, Linear systems, Inference algorithms, Prediction algorithms BibRef

Han, J., Yang, L., Zhang, D., Chang, X., Liang, X.,
Reinforcement Cutting-Agent Learning for Video Object Segmentation,
CVPR18(9080-9089)
IEEE DOI 1812
Object segmentation, Task analysis, Search problems, Computer vision, Decision making, Tracking BibRef

Li, Y., Shi, J., Lin, D.,
Low-Latency Video Semantic Segmentation,
CVPR18(5997-6005)
IEEE DOI 1812
Semantics, Image segmentation, Convolution, Kernel, Task analysis, Feeds, Streaming media BibRef

Xu, Y., Fu, T., Yang, H., Lee, C.,
Dynamic Video Segmentation Network,
CVPR18(6556-6565)
IEEE DOI 1812
Semantics, Image segmentation, Feature extraction, Computer architecture, Video sequences, Acceleration, Adaptive scheduling BibRef

Yi, R.[Ran], Liu, Y.J.[Yong-Jin], Lai, Y.K.[Yu-Kun],
Content-Sensitive Supervoxels via Uniform Tessellations on Video Manifolds,
CVPR18(646-655)
IEEE DOI 1812
Voxesl, coherent in apprarance and motion. Streaming media, Cascading style sheets, Manifolds, Spatiotemporal phenomena, Image color analysis, Generators, BibRef

Chen, Y., Pont-Tuset, J., Montes, A., Van Gool, L.J.,
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning,
CVPR18(1189-1198)
IEEE DOI 1812
Object segmentation, Measurement, Task analysis, Adaptive optics, Feature extraction, Streaming media BibRef

Xiao, H., Feng, J., Lin, G., Liu, Y., Zhang, M.,
MoNet: Deep Motion Exploitation for Video Object Segmentation,
CVPR18(1140-1148)
IEEE DOI 1812
Motion segmentation, Feature extraction, Transforms, Optical imaging, Optical network units, Object segmentation, Optical propagation BibRef

Nilsson, D., Sminchisescu, C.,
Semantic Video Segmentation by Gated Recurrent Flow Propagation,
CVPR18(6819-6828)
IEEE DOI 1812
Semantics, Logic gates, Optical network units, Image segmentation, Adaptation models, Computer architecture, Motion segmentation BibRef

Sokeh, H.S., Argyriou, V., Monekosso, D., Remagnino, P.,
Superframes, A Temporal Video Segmentation,
ICPR18(566-571)
IEEE DOI 1812
Clustering algorithms, Motion segmentation, Histograms, Databases, Image segmentation, Optical imaging, Video sequences BibRef

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

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

Xiao, F.[Fanyi], Lee, Y.J.[Yong Jae],
Video Object Detection with an Aligned Spatial-Temporal Memory,
ECCV18(VIII: 494-510).
Springer DOI 1810
BibRef

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

Wang, S.[Shiyao], Zhou, Y.C.[Yu-Cong], Yan, J.[Junjie], Deng, Z.D.[Zhi-Dong],
Fully Motion-Aware Network for Video Object Detection,
ECCV18(XIII: 557-573).
Springer DOI 1810
BibRef

Xu, J., Song, L., Xie, R.,
Two-stream deep encoder-decoder architecture for fully automatic video object segmentation,
VCIP17(1-4)
IEEE DOI 1804
image segmentation, image sequences, learning (artificial intelligence), video signal processing, motion segmentation BibRef

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

Yuan, Y., Liang, X., Wang, X., Yeung, D.Y., Gupta, A.,
Temporal Dynamic Graph LSTM for Action-Driven Video Object Detection,
ICCV17(1819-1828)
IEEE DOI 1802
LSTM: Long Short-Term Memory. graph theory, image classification, learning (artificial intelligence), object detection, Visualization BibRef

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

Hong, S., Yeo, D., Kwak, S., Lee, H., Han, B.,
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos,
CVPR17(2224-2232)
IEEE DOI 1711
Decoding, Image segmentation, Motion segmentation, Optimization, Semantics, Videos BibRef

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

Mahasseni, B., Todorovic, S., Fern, A.,
Budget-Aware Deep Semantic Video Segmentation,
CVPR17(2077-2086)
IEEE DOI 1711
Computer architecture, Feature extraction, Interpolation, Labeling, Runtime, Semantics, Training BibRef

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

Pathak, D., Girshick, R., Dollár, P.[Piotr], Darrell, T.J., Hariharan, B.,
Learning Features by Watching Objects Move,
CVPR17(6024-6033)
IEEE DOI 1711
Image segmentation, Motion segmentation, Object detection, Training, Unsupervised learning, Videos BibRef

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

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

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

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

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

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

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

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

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

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

Vishnyakov, B.V., Sidyakin, S.V., Vizilter, Y.V.,
Diffusion Background Model for Moving Objects Detection,
PTVSBB15(65-71).
DOI Link 1508
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

Faktor, A.[Alon], Irani, M.[Michal],
Video Segmentation by Non-Local Consensus voting,
BMVC14(xx-yy).
HTML Version. 1410
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Wang, R.[Rui], Bunyak, F.[Filiz], Seetharaman, G.[Guna], Palaniappan, K.[Kannappan],
Static and Moving Object Detection Using Flux Tensor with Split Gaussian Models,
CDW14(420-424)
IEEE DOI 1409
Gaussian model BibRef

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

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

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

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

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

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

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

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

Verbeke, N.[Nicolas], Vincent, N.[Nicole],
A PCA-Based Technique to Detect Moving Objects,
SCIA07(641-650).
Springer DOI 0706
BibRef

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

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

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

Yamazaki, M.[Masaki], Xu, G.[Gang], Chen, Y.W.[Yen-Wei],
Detection of Moving Objects by Independent Component Analysis,
ACCV06(II:467-478).
Springer DOI 0601
See also Separating Reflections from Images Using Kernel Independent Component Analysis. BibRef

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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],
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Carminati, L., Benois-Pineau, J.,
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ICIP05(III: 113-116).
IEEE DOI 0512
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Dupont, R.[Romain], Paragios, N.[Nikos], Keriven, R.[Renaud], Fuchs, P.[Phillipe],
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EMMCVPR05(220-234).
Springer DOI 0601
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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
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Wang, Y.[Yang], Ji, Q.A.[Qi-Ang],
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CVPR05(I: 264-270).
IEEE DOI 0507
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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
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Barbu, A.[Adrian], Zhu, S.C.[Song Chun],
On the Relationship Between Image and Motion Segmentation,
SCVMA04(51-63).
Springer DOI 0405
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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
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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
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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
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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
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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).
IEEE DOI 0411
Moving feature detector. BibRef

Tweed, D.,
Estimating rigid motions via the conformal model of Euclidean space,
ICPR04(II: 171-174).
IEEE DOI 0409
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Nair, V., Clark, J.J.,
An unsupervised, online learning framework for moving object detection,
CVPR04(II: 317-324).
IEEE DOI 0408
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Toth, D., Aach, T.,
Detection and recognition of moving objects using statistical motion detection and Fourier descriptors,
CIAP03(430-435).
IEEE DOI 0310
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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
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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

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

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


Last update:Sep 28, 2020 at 12:04:43