19.3.4.8 Motion Segmentation by Tracking, Trajectories, Region Based Tracking

Chapter Contents (Back)
Motion Segmentation. Trajectory Analysis. Motion Detection.

Liu, Y., Zheng, Y.F.,
Video Object Segmentation and Tracking Using psi-Learning Classification,
CirSysVideo(15), No. 7, July 2005, pp. 885-899.
IEEE DOI 0508
BibRef

Shen, C.F.[Chun-Feng], Lin, X.Y.[Xue-Yin], Shi, Y.C.[Yuan-Chun],
Moving object tracking under varying illumination conditions,
PRL(27), No. 14, 15 October 2006, pp. 1632-1643.
Elsevier DOI 0609
BibRef
Fusion of Texture Variation and On-Line Color Sampling for Moving Object Detection Under Varying Chromatic Illumination,
ACCV06(I:90-99).
Springer DOI 0601
Tracking, Color model, Texture model, Illumination variation, Level set BibRef

Vidal, R.[René], Ma, Y.[Yi],
A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation and Estimation,
JMIV(25), No. 3, October 2006, pp. 403-421.
Springer DOI 0611
BibRef
Earlier:
A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation,
ECCV04(Vol I: 1-15).
Springer DOI 0405
Award, ECCV, HM. BibRef

Rao, S.R.[Shankar R.], Tron, R.[Roberto], Vidal, R.[Rene], Ma, Y.[Yi],
Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories,
PAMI(32), No. 10, October 2010, pp. 1832-1845.
IEEE DOI 1008
Code, Motion Segmentation. BibRef
Earlier:
Motion segmentation via robust subspace separation in the presence of outlying, incomplete, or corrupted trajectories,
CVPR08(1-8).
IEEE DOI 0806
Segmenting tracked trajectories, occlusions, deformations lead to problems. Develop robust separation scheme to deal with these issues. Related to lossy compression. Code is available.
WWW Link. BibRef

Vidal, R.[René], Tron, R.[Roberto], Hartley, R.I.[Richard I.],
Multiframe Motion Segmentation with Missing Data Using PowerFactorization and GPCA,
IJCV(79), No. 1, August 2008, pp. xx-yy.
Springer DOI 0804
BibRef
Earlier: A1, A3, Only:
Motion segmentation with missing data using powerfactorization and GPCA,
CVPR04(II: 310-316).
IEEE DOI 0408

See also Generalized Principal Component Analysis (GPCA).
See also Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and its Applications.
See also Three-View Multibody Structure from Motion. BibRef

Vidal, R., Sastry, S.,
Optimal segmentation of dynamic scenes from two perspective views,
CVPR03(II: 281-286).
IEEE DOI 0307
BibRef
Earlier:
Segmentation of dynamic scenes from image intensities,
Motion02(44-49).
IEEE DOI 0303
BibRef

Xu, F.[Feng], Lam, K.M.[Kin-Man], Dai, Q.H.[Qiong-Hai],
Video-object segmentation and 3D-trajectory estimation for monocular video sequences,
IVC(29), No. 2-3, February 2011, pp. 190-205.
Elsevier DOI 1101
2D-to-3D video conversion, 3D trajectory estimation, Video-object segmentation BibRef

Wang, Z.J.[Zhi-Jie], Salah, M.B.[Mohamed Ben], Zhang, H.[Hong],
Object joint detection and tracking using adaptive multiple motion models,
VC(30), No. 2, February 2014, pp. 173-187.
WWW Link. 1402
BibRef
Earlier: A1, A3, Only:
Object Detection with Multiple Motion Models,
ACCV09(III: 183-192).
Springer DOI 0909
BibRef

Liwicki, S.[Stephan], Zafeiriou, S.P.[Stefanos P.], Pantic, M.[Maja],
Online Kernel Slow Feature Analysis for Temporal Video Segmentation and Tracking,
IP(24), No. 10, October 2015, pp. 2955-2970.
IEEE DOI 1507
BibRef
Earlier:
Incremental Slow Feature Analysis with Indefinite Kernel for Online Temporal Video Segmentation,
ACCV12(II:162-176).
Springer DOI 1304
Eigenvalues and eigenfunctions
See also Learning Slow Features for Behaviour Analysis.
See also Slow Feature Analysis for Human Action Recognition. BibRef

Chen, L., Shen, J., Wang, W., Ni, B.,
Video Object Segmentation Via Dense Trajectories,
MultMed(17), No. 12, December 2015, pp. 2225-2234.
IEEE DOI 1512
Clustering algorithms BibRef

Luo, Y.[Ye], Yuan, J.S.[Jun-Song], Lu, J.W.[Jian-Wei],
Finding spatio-temporal salient paths for video objects discovery,
JVCIR(38), No. 1, 2016, pp. 45-54.
Elsevier DOI 1605
Spatio-temporal path BibRef

Mahmood, M.H.[Muhammad Habib], Díez, Y.[Yago], Salvi, J.[Joaquim], Lladó, X.[Xavier],
A collection of challenging motion segmentation benchmark datasets,
PR(61), No. 1, 2017, pp. 1-14.
Elsevier DOI 1705
Dataset, Motion Segmentation. Motion segmentation BibRef

Mahmood, M.H.[Muhammad Habib], Zappella, L.[Luca], Díez, Y.[Yago], Salvi, J.[Joaquim], Lladó, X.[Xavier],
A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15),
IbPRIA15(463-470).
Springer DOI 1506
Dataset, Motion Segmentation. BibRef

Wang, Y., Liu, Y., Blasch, E., Ling, H.,
Simultaneous Trajectory Association and Clustering for Motion Segmentation,
SPLetters(25), No. 1, January 2018, pp. 145-149.
IEEE DOI 1801
image motion analysis, image segmentation, image sequences, iterative methods, optimisation, pattern clustering, tensors, tensor-based association BibRef

Lu, Y.C.[Yu-Cheng], Kim, D.W.[Dong-Wook], Kim, S.[Sesong], Jung, S.W.[Seung-Won],
Foreground extraction via dual-side cameras on a mobile device using long short-term trajectory analysis,
IVC(90), 2019, pp. 103808.
Elsevier DOI 1912
Dual-side cameras, Foreground extraction, Gaussian mixture model, Trajectory analysis BibRef

Fan, Y.C.[Ying-Chun], Han, H.[Hong], Tang, Y.L.[Yu-Liang], Zhi, T.[Tao],
Dynamic objects elimination in SLAM based on image fusion,
PRL(127), 2019, pp. 191-201.
Elsevier DOI 1911
SLAM, Dynamic objects, Trajectory, Navigate, Image fusion BibRef


Vu, T.H.[Tuan Hung], Choi, W.G.[Won-Gun], Schulter, S.[Samuel], Chandraker, M.[Manmohan],
Memory Warps for Long-Term Online Video Representations and Anticipation,
WACV19(1156-1165)
IEEE DOI 1904
feature extraction, image motion analysis, image representation, multi-threading, object detection, video signal processing, Visualization BibRef

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

Zhai, M.Y.[Meng-Yao], Chen, L.[Lei], Li, J.L.[Jin-Ling], Khodabandeh, M.[Mehran], Mori, G.[Greg],
Object detection in surveillance video from dense trajectories,
MVA15(535-538)
IEEE DOI 1507
Bandwidth BibRef

Shi, F.[Feng], Zhou, Z.[Zhong], Xiao, J.J.[Jiang-Jian], Wu, W.[Wei],
Robust Trajectory Clustering for Motion Segmentation,
ICCV13(3088-3095)
IEEE DOI 1403
BibRef

Trichet, R.[Remi], Nevatia, R.[Ramakant], Burns, B.[Brian],
Video event classification with temporal partitioning,
AVSS15(1-6)
IEEE DOI 1511
Animals BibRef

Trichet, R.[Remi], Nevatia, R.[Ramakant],
Video segmentation and feature co-occurrences for activity classification,
WACV14(385-392)
IEEE DOI 1406
BibRef
Earlier:
Video segmentation with spatio-temporal tubes,
AVSS13(330-335)
IEEE DOI 1311
Long-term temporal interactions among objects. based on dense trajectory clustering. Context. BibRef

Narayan, S.[Sanath], Ramakrishnan, K.R.,
Motion segmentation using curve fitting on Lagrangian particle trajectories,
ICPR12(3692-3695).
WWW Link. 1302
BibRef

Zhang, G.[Geng], Yuan, Z.[Zejian], Chen, D.P.[Da-Peng], Liu, Y.H.[Yue-Hu], Zheng, N.N.[Nan-Ning],
Video object segmentation by clustering region trajectories,
ICPR12(2598-2601).
WWW Link. 1302
BibRef

Vishnyakov, B.V., Vizilter, Y.V., Knyaz, V.,
Spectrum-based Object Detection and Tracking Technique for Digital Video Surveillance,
ISPRS12(XXXIX-B3:579-583).
DOI Link 1209
BibRef

Kim, C., Li, F.X.[Fu-Xin], Ciptadi, A., Rehg, J.M.,
Multiple Hypothesis Tracking Revisited,
ICCV15(4696-4704)
IEEE DOI 1602
Computational modeling BibRef

Li, F.X.[Fu-Xin], Kim, T.Y.[Tae-Young], Humayun, A.[Ahmad], Tsai, D.[David], Rehg, J.M.[James M.],
Video Segmentation by Tracking Many Figure-Ground Segments,
ICCV13(2192-2199)
IEEE DOI 1403
CPMC BibRef

Beaugendre, A.[Axel], Zhang, C.Y.[Chen-Yuan], Xu, J.[Jiu], Goto, S.[Satoshi],
Enhanced moving object detection using tracking system for video surveillance purposes,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Jain, R., Sankar, K.P., Jawahar, C.V.,
Interpolation Based Tracking for Fast Object Detection in Videos,
NCVPRIPG11(102-105).
IEEE DOI 1205
BibRef

Huang, C.C.[Ching-Chun], Wang, S.J.[Sheng-Jyh],
A cascaded hierarchical framework for moving object detection and tracking,
ICIP10(4629-4632).
IEEE DOI 1009
BibRef

Lu, W.C.[Wang-Chou], Wang, Y.C.F., Chen, C.S.[Chu-Song],
Learning Dense Optical-Flow Trajectory Patterns for Video Object Extraction,
AVSS10(315-322).
IEEE DOI 1009
BibRef

Pinho da Silva, N.[Nuno], Costeira, J.P.[Joaao Paulo],
The Normalized Subspace Inclusion: Robust clustering of motion subspaces,
ICCV09(1444-1450).
IEEE DOI 0909
point trajectories for clustering into objects. BibRef

Baugh, G.[Gary], Kokaram, A.[Anil],
Semi-automatic motion based segmentation using long term motion trajectories,
ICIP10(3009-3012).
IEEE DOI 1009
BibRef

Hernandez, J.[Josue], Morita, H.[Hiroshi], Nakano-Miytake, M.[Mariko], Perez-Meana, H.M.[Hector M.],
Movement Detection and Tracking Using Video Frames,
CIARP09(1054-1061).
Springer DOI 0911
BibRef

Guler, S.[Sadiye], Silverstein, J.A.[Jason A.], Pushee, I.H.[Ian H.],
Stationary objects in multiple object tracking,
AVSBS07(248-253).
IEEE DOI 0709
BibRef

Huang, K.Q.[Kai-Qi], Wang, L.S.[Liang-Sheng], Tan, T.N.[Tie-Niu],
Detecting and Tracking Distant Objects at Night Based on Human Visual System,
ACCV06(II:822-831).
Springer DOI 0601
Measure spatio-temporal contrast change BibRef

Xu, M.[Min], Niu, R.X.[Rui-Xin], Varshney, P.K.,
Detection and tracking of moving objects in image sequences with varying illumination,
ICIP04(IV: 2595-2598).
IEEE DOI 0505
BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Real-Time Motion Segmentation, Hardware for Motion Detection .


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