Efficient extraction of human motion volumes by tracking

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2010, Pages 655-662

  Niebles, Juan Carlos ^a,b   Han, Bohyung ^c   Fei Fei, Li ^d  

^a PRINCETON UNIVERSITY   (United States)

^b UNIVERSIDAD DEL NORTE   (Colombia)

^c Ulsan National Institute of Science and Technology   (South Korea)

^d Stanford University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPEARANCE BASED; BELIEF PROPAGATION; DATA SETS; EFFICIENT METHOD; HUMAN BODIES; HUMAN MOTIONS; IMAGE REGIONS; LEVEL SETS; PEDESTRIAN DETECTION; SHAPE PRIORS; SPATIO-TEMPORAL; TEMPORAL PROPAGATION; TOP DOWN MODELS; TOPDOWN; YOUTUBE;

COMPUTER VISION;

EID: 77955990095     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5540152     Document Type: Conference Paper

References (25)

1. S. Baker and I. Matthews. Lucas-Kanade 20 Years On: A Unifying Framework. IJCV, 56(3):221-255, 2004.
2. C. Bibby and I. Reid. Robust real-time visual tracking using pixel-wise posteriors. In ECCV, 2008.
3. D. Cremers. Dynamical statistical shape priors for level set-based tracking. IEEE TPAMI, 28(8):1262-1273, 2006.
4. D. Cremers, M. Rousson, and R. Deriche. A review of statistical approaches to level set segmentation: Integrating color, texture, motion and shape. IJCV, 72(2):195-215, 2007.
5. J. Deutscher, A. Blake, and I. Reid. Articulated body motion capture by annealed particle filtering. In CVPR, 2000.
6. P. Felzenszwalb and D. Huttenlocher. Pictorial structures for object recognition. IJCV, 61(1):55-79, 2005.
7. V. Ferrari, M. Marin-Jimenez, and A. Zisserman. Progressive search space reduction for human pose estimation. In CVPR, 2008.
8. D. A. Forsyth, O. Arikan, L. Ikemoto, J. O'Brien, and D. Ramanan. Computational studies of human motion: Part 1, tracking and motion synthesis. Foundations and Trends in Computer Graphics and Vision, 1:77-254, 2005.
9. T. Han, H. Ning, and T. Huang. Efficient nonparametric belief propagation with application to articulated body tracking. In CVPR, pages 214-221, 2006.
10. X. Lan and D. Huttenlocher. A unified spatio-temporal articulated model for tracking. In ICCV, volume I, pages 722-729, 2004.
11. I. Laptev. Improvements of object detection using boosted histograms. In BMVC, volume III, pages 949-958, 2006.
12. C.-S. Lee and A. Elgammal. Modeling view and posture manifolds for tracking. In ICCV, 2007.
13. C. Li, C. Xu, C. Gui, and M. Fox. Level set evolution without re-initialization: A new variational formulation. In CVPR, pages 430-436, 2005.
14. J. Niebles, B. Han, A. Ferencz, and L. Fei-Fei. Extracting moving people from internet videos. In ECCV, 2008.
15. N. Paragios and R. Deriche. Geodesic active regions and level set methods for motion estimation and tracking. CVIU, 97(3):259-282, 2005.
16. D. Ramanan. Learning to parse images of articulated objects. In NIPS, 2006.
17. D. Ramanan, D. Forsyth, and A. Zisserman. Tracking people by learning their appearance. IEEE TPAMI, 29(1):65-81, 2007.
18. X. Ren and J. Malik. Tracking as repeated figure/ground segmentation. In CVPR, 2007.
19. H. Sidenbladh, M. Black, and L. Sigal. Implicit probabilistic models of human motion for synthesis and tracking. In ECCV, 2002.
20. L. Sigal, S. Bhatia, S. Roth, M. Black, and M. Isard. Tracking loose-limbed people. In CVPR, 2004.
21. C. Sminchisescu, A. Kanaujia, Z. Li, and D. Metaxas. Discriminative density propagation for 3d human motion estimation. In CVPR, 2005.
22. C. Sminchisescu and B. Triggs. Covariance scaled sampling for monocular 3D body tracking. In CVPR, 2001.
23. D. Tran and A. Sorokin. Human activity recognition with metric learning. In ECCV, 2008.
24. L.Wang, J. Shi, G. Song, and I. Shen. Object detection combining recognition and segmentation. In ACCV, volume I, pages 189-199, 2007.
25. A. Yilmaz, X. Li, and M. Shah. Contour-based object tracking with occlusion handling in video acquired using mobile cameras. IEEE TPAMI, 26(11):1531-1536, 2004.