A Set theoretical method for video synopsis

Proceedings of the 1st International ACM Conference on Multimedia Information Retrieval, MIR2008, Co-located with the 2008 ACM International Conference on Multimedia, MM'08

Volumn , Issue , 2008, Pages 366-370

  Xu, Min ^a   Li, Stan Z ^b   Li, Bin ^a   Yuan, Xiao Tong ^b   Xiang, Shi Ming ^b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

Mean shift; Object start time programming; Set theory; Video synopsis

Indexed keywords

LOCAL OPTIMA; MEAN SHIFT; MOVING OBJECTS; SPATIAL TEMPORALS; VIDEO ACTIVITY; VISUAL INFORMATION;

INFORMATION RETRIEVAL; INFORMATION SERVICES; METHOD OF MOMENTS; SET THEORY; TRACKING (POSITION); VECTOR QUANTIZATION; VISUAL COMMUNICATION;

MULTIMEDIA SYSTEMS;

EID: 70450270839     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1460096.1460156     Document Type: Conference Paper

References (11)

1. D. Cimaniciu, V. Ramesh, and P. Meer. Kernel-based object tracking. IEEE Trans on Pattern Analysis and Machine Intelligence, 25(5): 564-577, 2003.
2. C. Kim and J. Hwang. An integrated scheme for object-based video abstraction. In Proc. of the 8th ACM Int'l Conf. on Multimedia, pages 303-311, 2000.
3. S. Z. Li. Robustizing robust M-estimation using deterministic annealing. Pattern Recognition, 29(1): 159-166, 1996.
4. J. Nam and A.Tewfik. Video abstract of video. In Proc. of 3rd IEEE Workshop on Multimedia Signal Processing, pages 117-122, September 1999.
5. N. Petrovic, N. Jojic, and T. Huang. Adaptive video fast forward. Multimedia Tools and Applications, 26(3): 327-344, 2005.
6. A. Rav-Acha, Y. Pritch, A.Gutman, and S. Peleg. Web synopsis: Peeking around the world. In Proc. of IEEE on International Conference on Computer Vision, October 2007.
7. A. Rav-Acha, Y. Pritch, and S. Peleg. Making a long video short: Dynamic video synopsis. In Proc. of 2006 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, pages 435-441, June 2006.
8. A. M. Smith and T. Kanade. Video skimming and characterization through the combination of image and language understanding. In Proc. of IEEE Workshop on Content-Based Access of Image and Video Database, pages 61-70, 1998.
9. C. Stauffer and W. Grimson. Learning patterns of activity using real-time tracking. IEEE Trans on Pattern Analysis and Machine Intelligence, 8(22): 747-757, 2000.
10. T.Yang, S. Z. Li, Q. Pan, and J. Li. Real-time multiple objects tracking with occlusion handling in dynamic scenes. In Proc. of 2005 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, pages 970-975, June 2005.
11. X. Zhu, X. Wu, J. Fan, A. K. Elmagarmid, and W. G. Aref. Exploring video content structure for hierarchical summarization. Multimedia Syst., 10(2): 98-115, 2004.