Estimating Tracking Sources and Sinks

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 4, Issue , 2003, Pages

  Stauffer, Chris ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAMERAS; COMPUTER VISION; LOCATION;

ACTIVITY LEVELS; COUPLED PROBLEMS; MODEL SELECTION CRITERIA; NON-OVERLAPPING CAMERA VIEWS; NUMBER OF SOURCES; TRACKING FAILURE; TRACKING SEQUENCE; TRACKING SYSTEM;

PATTERN RECOGNITION;

EID: 84954434547     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2003.10036     Document Type: Conference Paper

References (6)

1. Timothy Huang and Stuart Russell. Object identification in a bayesian context. In Proc. Fifteenth International Joint Conference on Artificial Intelligence (IJCAI97), Nagoya, Japan, 1997.
2. Michael Isard and Andrew Blake. Condensation - conditional density propagation for visual tracking. Int. Journal of Computer Vision, 29(1):5-28, 1998.
3. Yuri Ivanov, Chris Stauffer, Aaron Bobick, and W.E.L. Grimson. Video surveillance of interactions. Fort Collins, Colorado, June 26, 1999.
4. Neil Johnson and David C. Hogg. Learning the distribution of object trajectories for event recognition. In Pycock D., editor, British Machine Vision Conference (BMVA), pages 583-592, September 1995.
5. Hanna Pasula, Stuart J. Russell, Michael Ostland, and Yaacov Ritov. Tracking many objects with many sensors. In IJCAI99, pages 1160-1171, 1999.
6. Chris Stauffer and W.E.L.Grimson. Learning patterns of activity using real-time tracking. IEEE Trans. on Pattern Analysis and Machine Intelligence, 22(8), August 2000.