Person count localization in videos from noisy foreground and detections

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

Volumn 07-12-June-2015, Issue , 2015, Pages 1364-1372

  Chen, Sheng ^a   Fern, Alan ^a   Todorovic, Sinisa ^a  

^a OREGON STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; FLOW GRAPHS; GRAPHIC METHODS; INTEGER PROGRAMMING;

AMERICAN FOOTBALLS; FOREGROUND SEGMENTATION; INTEGRITY CONSTRAINTS; PEOPLE DETECTION; PERSON DETECTION; PROBLEM FORMULATION; SEVERE OCCLUSIONS; VIDEO UNDERSTANDING;

PATTERN RECOGNITION;

EID: 84959251343     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298742     Document Type: Conference Paper

References (26)

1. J. Aggarwal and M. Ryoo. Human activity analysis: A review. ACM Comput. Surv, 2011
2. M. Amer and S. Todorovic. Sum-product networks for modeling activities with stochastic structure. In CVPR, 2012
3. M. Andriluka, S. Roth, and B. Schiele. People-tracking-bydetection and people-detection-by-tracking. In CVPR, 2008
4. B. Antic and B. Ommer. Learning latent constituents for recognition of group activities in video. In ECCV, 2012
5. A. B., C. Z.-S. John, and L. N. Vasconcelos. Privacy preserving crowd monitoring: Counting people without people models or tracking. In CVPR, 2008
6. A. B. Chan and N. Vasconcelos. Counting people with lowlevel features and Bayesian regression. In TIP, 2012
7. W. Choi and S. Savarese. Understanding collective activities of people from videos. In PAMI, 2014
8. Y. Cong, H. Gong, S.-C. Zhu, and Y. Tang. Flow mosaicking: Realtime pedestrian counting without scene-specific learning. In CVPR, 2009
9. P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part based models. PAMI, 32(9):1627-1645, 2010
10. W. Ge, T. R. Collins, and R. B. Ruback. Vision-based analysis of small groups in pedestrian crowds. IEEE TPAMI, 2012
11. J. Henriques and J. Caseiro R., Batista. Globally optimal solution to multi-object tracking with merged measurements. In ICCV, 2011
12. Y. Huang and I. Essa. Tracking multiple objects through occlusions. In CVPR, 2005
13. S. D. Khan, G. Vizzari, S. Bandini, and S. Basalamah. Detecting dominant motion flows and people counting in high density crowds. In WSCG, 2014
14. D. Kong, D. Gray, and H. Tao. A viewpoint invariant approach for crowd counting. In ICPR, 2012
15. C.-H. Kuo, C. Huang, and R. Nevatia. Multi-target tracking by on-line learned discriminative appearance models. In CVPR, 2010
16. T. Lan, L. Sigal, and G. Mori. Social roles in hierarchical models for human activity recognition. In CVPR, 2012
17. V. Lempitsky and A. Zisserman. Learning to count objects in images. In NIPS, 2010
18. Z. Ma and A. B. Chan. Crossing the line: Crowd counting by integer programming with local features. In CVPR, 2013
19. P. Nillius, J. Sullivan, and S. Carlsson. Multi-target trackinglinking identities using Bayesian network inference. In CVPR, 2006
20. D. Ryan, S. Denman, C. Fookes, and S. Sridharan. Crowd counting using multiple local features. In DICTA, 2009
21. M. Schiegg, P. Hanslovsky, B. X. Kausler, L. Hufnagel, and F. A. Hamprecht. Conservation tracking. In ICCV, 2013
22. G. Shu, A. Dehghan, O. Oreifej, E. Hand, and M. Shah. Partbased multiple-person tracking with partial occlusion handling. In CVPR, 2012
23. L. Sun, H. Ai, and S. Lao. Activity group localization by modeling the relations among participants. In ECCV, 2014
24. J. Xing, H. Ai, and S. Lao. Multi-object tracking through occlusions by local tracklets filtering and global tracklets association with detection responses. In CVPR, 2009
25. B. Yang and R. Nevatia. Online learned discriminative part-based appearance models for multi-human tracking. In ECCV, 2012
26. K. Zhang, L. Zhang, and M.-H. Yang. Real-time compressive tracking. In ECCV, 2012.