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0005
BibRef
Earlier:
Moving Target Detection in Infrared Imagery Using a Regularised CDWT
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BibRef
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DOI Link
0301
BibRef
Earlier: A3, A1, Only:
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0711
See also Distances between frequency features for 3D visual pattern partitioning. Spatio-temporal energy filtering, Feature integration;
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BibRef
Yang, H.[Hong],
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0806
BibRef
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0901
BibRef
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IEEE DOI
0502
Surveillance, Direction maps, Dominant direction, Event detection;
Spatiotemporal analysis, Motion analysis
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1509
computer vision
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1108
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Earlier: A1, A4, A3, A2, A5, A6:
Efficient Dense Scene Flow from Sparse or Dense Stereo Data,
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Springer DOI
0810
See also Video Super Resolution Using Duality Based TV-L1 Optical Flow.
BibRef
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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
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ICCV11(1583-1590).
IEEE DOI
1201
Adaptive optics
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Quiroga, J.[Julian],
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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
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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],
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Springer2011.
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1109
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Wedel, A.[Andreas],
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IEEE DOI
0811
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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
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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
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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
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DAGM07(112-121).
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0709
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Wu, B.[Bo],
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1305
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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
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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],
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Consistent Video Saliency Using Local Gradient Flow Optimization and
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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,
video co-segmentation
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Wang, W.G.[Wen-Guan],
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Shao, L.[Ling],
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Correspondence Driven Saliency Transfer,
IP(25), No. 11, November 2016, pp. 5025-5034.
IEEE DOI
1610
estimation theory.
BibRef
Wang, W.G.[Wen-Guan],
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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
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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
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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.,
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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
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ICPR12(3640-3643).
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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.J.[Meng-Jia],
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
Ray, K.S.[Kumar S.],
Chakraborty, S.[Soma],
Object detection by spatio-temporal analysis and tracking of the
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JVCIR(58), 2019, pp. 662-674.
Elsevier DOI
1901
Variable background, Object detection, Gabor filter,
Spatio-temporal analysis, Minimum Spanning Tree (MST),
Occlusion
BibRef
Peng, Y.X.[Yu-Xin],
Zhao, Y.Z.[Yun-Zhen],
Zhang, J.C.[Jun-Chao],
Two-Stream Collaborative Learning With Spatial-Temporal Attention for
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CirSysVideo(29), No. 3, March 2019, pp. 773-786.
IEEE DOI
1903
The static frame and optical flow.
Feature extraction, Adaptation models, Video sequences,
Collaboration, Semantics, Collaborative work, Weapons,
adaptively weighted learning
BibRef
Wu, R.X.[Rui-Xu],
Liu, Y.L.[Yan-Li],
Wang, X.G.[Xiao-Gang],
Yang, P.L.[Pei-Lin],
Visual tracking based on spatiotemporal transformer and fusion
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IVC(148), 2024, pp. 105107.
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2407
Visual tracking, Flatten transformer, Spatiotemporal, Sequence fusion
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Sameni, S.[Sepehr],
Jenni, S.[Simon],
Favaro, P.[Paolo],
Spatio-Temporal Crop Aggregation for Video Representation Learning,
ICCV23(5641-5651)
IEEE DOI
2401
BibRef
Mahendran, A.[Aravindh],
Thewlis, J.[James],
Vedaldi, A.[Andrea],
Cross Pixel Optical-Flow Similarity for Self-supervised Learning,
ACCV18(V:99-116).
Springer DOI
1906
BibRef
Earlier:
Self-supervised Segmentation by Grouping Optical-Flow,
POCV18(V:528-534).
Springer DOI
1905
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
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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
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EMMCVPR17(93-108).
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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
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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],
Iterative Residual Refinement for Joint Optical Flow and Occlusion
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CVPR19(5747-5756).
IEEE DOI
2002
BibRef
Earlier:
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
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Teney, D.[Damien],
Brown, M.[Matthew],
Segmentation of Dynamic Scenes with Distributions of Spatiotemporally
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BMVC14(xx-yy).
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1410
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Mukherjee, D.[Dibyendu],
Wu, Q.M.J.[Q.M. Jonathan],
Streaming spatio-temporal video segmentation using Gaussian Mixture
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ICIP14(4388-4392)
IEEE DOI
1502
Clustering algorithms
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Morimitsu, H.[Henrique],
Cesar, Jr., R.M.[Roberto M.],
Bloch, I.[Isabelle],
A Spatio-temporal Approach for Multiple Object Detection in Videos
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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)
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1412
BibRef
Earlier:
A performance evaluation of fusion techniques for spatio-temporal
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ICIP13(3924-3928)
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1402
Computational modeling.
Spatio-temporal saliency
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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
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Cheng, H.T.T.[Hsien-Ting Tim],
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Exploiting nonlocal spatiotemporal structure for video segmentation,
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1208
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Xie, D.F.[Dan-Feng],
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ICPR12(3132-3135).
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Spatio-temporal LBP Based Moving Object Segmentation in Compressed
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AVSS12(252-257).
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1211
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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).
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1109
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Moving object detection based on T-test combined with kirsch operator,
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Object Extraction by Spatio-Temporal Assembling,
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Graph-Based Spatio-temporal Region Extraction,
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0610
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Spatio-temporal Segmentation Using Laser-scanner and Video Sequences,
DAGM04(367-374).
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0505
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Detection of moving objects using a spatiotemporal representation,
ICPR96(I: 483-487).
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9608
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Hirai, T.,
Sasakawa, K.,
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9208
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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 .