18.3.4.1 Spatio-Temporal Motion Segmentation, Flow Based Segmentation

Chapter Contents (Back)
Motion Segmentation. Spatio-Temporal Segmentation. Spatiotemporal.

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

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

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

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

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

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

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.[Peter], Malik, J.[Jitendra], Brox, T.[Thomas],
Segmentation of Moving Objects by Long Term Video Analysis,
PAMI(36), No. 6, June 2014, pp. 1187-1200.
IEEE DOI 1406
BibRef
Earlier: A3, A2, Only:
Object Segmentation by Long Term Analysis of Point Trajectories,
ECCV10(V: 282-295).
Springer DOI 1009
BibRef
And: A1, A3, Only:
Higher order motion models and spectral clustering,
CVPR12(614-621).
IEEE DOI 1208
BibRef
And: A1, A3, Only:
Object segmentation in video: A hierarchical variational approach for turning point trajectories into dense regions,
ICCV11(1583-1590).
IEEE DOI 1201
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

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

Wedel, A.[Andreas], Pock, T., Braun, J., Franke, U., Cremers, D.[Daniel],
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

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, 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

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],
Video Salient Object Detection via Fully Convolutional Networks,
IP(27), No. 1, January 2018, pp. 38-49.
IEEE DOI 1712
convolution, image annotation, image segmentation, image sequences, inference mechanisms, learning (artificial intelligence), synthetic video data BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Sun, H., Shao, L.[Ling],
Video Co-Saliency Guided Co-Segmentation,
CirSysVideo(28), No. 8, August 2018, pp. 1727-1736.
IEEE DOI 1808
Visualization, Silicon, Video sequences, Estimation, Motion segmentation, Proposals, Circuits and systems, video co-segmentation BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Shao, L.[Ling], Porikli, F.M.[Fatih Murat],
Correspondence Driven Saliency Transfer,
IP(25), No. 11, November 2016, pp. 5025-5034.
IEEE DOI 1610
estimation theory. BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Yang, R., Porikli, F.M.[Fatih Murat],
Saliency-Aware Video Object Segmentation,
PAMI(40), No. 1, January 2018, pp. 20-33.
IEEE DOI 1712
BibRef
Earlier: A1, A2, A4, Only:
Saliency-aware geodesic video object segmentation,
CVPR15(3395-3402)
IEEE DOI 1510
Image segmentation, Motion segmentation, Object segmentation, Proposals, Skeleton, Spatiotemporal phenomena, Trajectory, video object segmentation BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Xie, J., Porikli, F.M.[Fatih Murat],
Super-Trajectory for Video Segmentation,
ICCV17(1680-1688)
IEEE DOI 1802
image motion analysis, image representation, image segmentation, pattern clustering, spatiotemporal phenomena, Video sequences BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Li, X.L.[Xue-Long], Porikli, F.M.[Fatih M.],
Robust Video Object Cosegmentation,
IP(24), No. 10, October 2015, pp. 3137-3148.
IEEE DOI 1507
feature extraction BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Porikli, F.M.[Fatih M.],
Selective Video Object Cutout,
IP(26), No. 12, December 2017, pp. 5645-5655.
IEEE DOI 1710
pyramid histogram-based confidence map, structure information, uncertainty propagation, 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

Chen, C.Z.[Chengli-Zhao], Li, Y., Li, S.[Shuai], Qin, H.[Hong], Hao, A.[Aimin],
A Novel Bottom-Up Saliency Detection Method for Video With Dynamic Background,
SPLetters(25), No. 2, February 2018, pp. 154-158.
IEEE DOI 1802
cameras, filtering theory, image motion analysis, image sequences, object detection, video signal processing, video saliency 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

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

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


Tashlinskii, A.G., Smirnov, P.V., Tsaryov, M.G.,
Pixel-by-pixel Estimation of Scene Motion in Video,
PTVSBB17(61-65).
DOI Link 1805
BibRef

Erokhin, D.Y., Feldman, A.B., Korepanov, S.E.,
Detection And Tracking of Moving Objects with Real-time Onboard Vision System,
PTVSBB17(67-71).
DOI Link 1805
BibRef

Haque, N.[Nazrul], Reddy, N.D.[N. Dinesh], Krishna, M.[Madhava],
Temporal Semantic Motion Segmentation Using Spatio Temporal Optimization,
EMMCVPR17(93-108).
Springer DOI 1805
BibRef

Li, J., Zheng, A., Chen, X., Zhou, B.,
Primary Video Object Segmentation via Complementary CNNs and Neighborhood Reversible Flow,
ICCV17(1426-1434)
IEEE DOI 1802
convolution, image segmentation, neural nets, video signal processing, Complementary CNNs, Training BibRef

Taniai, T., Sinha, S.N., Sato, Y.,
Fast Multi-frame Stereo Scene Flow with Motion Segmentation,
CVPR17(6891-6900)
IEEE DOI 1711
Cameras, Motion segmentation, Optical imaging, BibRef

Du, Y., Yuan, C., Li, B., Hu, W., Maybank, S.J.[Steve J.],
Spatio-Temporal Self-Organizing Map Deep Network for Dynamic Object Detection from Videos,
CVPR17(4245-4254)
IEEE DOI 1711
Bayes methods, Dynamics, Kernel, Object detection, Self-organizing feature maps, Videos BibRef

Cheng, J., Tsai, Y.H.[Yi-Hsuan], Wang, S., Yang, M.H.[Ming-Hsuan],
SegFlow: Joint Learning for Video Object Segmentation and Optical Flow,
ICCV17(686-695)
IEEE DOI 1802
image segmentation, image sequences, learning (artificial intelligence), video signal processing, Training 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

Hur, J.[Junhwa], Roth, S.[Stefan],
MirrorFlow: Exploiting Symmetries in Joint Optical Flow and Occlusion Estimation,
ICCV17(312-321)
IEEE DOI 1802
BibRef
Earlier:
Joint Optical Flow and Temporally Consistent Semantic Segmentation,
CVRoads16(I: 163-177).
Springer DOI 1611
image sequences, inference mechanisms, optimisation, MirrorFlow, chicken-and-egg relation, forward-backward consistency, Transforms BibRef

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 17, 2018 at 09:12:27