Robust visual tracking for multiple targets

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3954 LNCS, Issue , 2006, Pages 107-118

  Cai, Yizherig ^a   De Freitag, Nando ^a   Little, James J ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CAMERAS; MOTION CONTROL; ROBUSTNESS (CONTROL SYSTEMS); TARGETS;

BACKGROUND CLUTTERS; CAMERA MOTION; MEANSHIFT ALGORITHM; MULTI-TARGET TRACKING; PARTICLE FILTERS;

TRACKING (POSITION);

EID: 33745809784     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11744085_9     Document Type: Conference Paper

References (20)

1. Isard, M., Blake, A.: CONDENSATION-Conditional Density Propagation for Visual Tracking. Internatinal Journal on Computer Vision 29(1) (1998) 5-28
2. Hue, C., Le Cadre, J., Pèrez, P.: Tracking Multiple Objects with Particle Filtering, In: IEEE Transactions on Aerospace and Electronic Systems. Volume 38, (2003) 313-318
3. Vermaak, J., Doucet, A., Pèrez, F.: Maintaining Multi-modality through Mixture Tracking. In: Internatinal Conference on Computer Vision. Volume II. (2003) 1110-1116
4. Okuma, K., Taleghani, A., de Freitas, J., Little, J., Lowe, D.: A Boosted Particle Filter: Multitarget Detection and Tracking, In: European Conference on Computer Vision, Volume I, (2004) 28-39
5. Viola, P., Jones, M.: Robust Real-Time Face Detection. Internatinal Journal on Computer Vision 57(2) (2004) 137-154
6. Kang, J., Cohen, I., Medioni, G.: Soccer Player Tracking across Uncalibrated Camera Streams. In: Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS) In Conjunction with ICCV. (2003) 172-179
7. Zhao, T., Nevatia, R.: Tracking Multiple Humans in Complex Situations. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(9) (2004) 1208-1221
8. MacCormick, J., Blake, A.: A Probabilistic Exclusion Principle for Tracking Multiple Objects. Internatinal Journal on Computer Vision 39(1) (2000) 57-71
9. Isard, M., MacCormick, J.: BraMBLe: A Bayesian Multiple-Blob Tracker. In: Internatinal Conference on Computer Vision. Volume II (2001) 34-41
10. Rittscher, J., Tu, P., Krahnstoever, N.: Simultaneous estimation of segmentation and shape. In: CVPR05. Volume II. (2005) 486-493
11. Shan, G., Wei, Y., Tan, T., Ojardias, F.: Real Time Hand Tracking by Combining Particle Filtering and Mean Shift. In: International Conference on Automatic Face and Gesture Recognition. (2004) 669-674
12. Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based Object Tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence 25(5) (2003) 564-577
13. Ferez, P., Hue, C., Vermaak, J., Gangnet, M.: Color-Based Probabilistic Tracking. In: European Conference on Computer Vision, Volume I. (2002) 661-675
14. Okuma, K., Little, J., Lowe, D.: Automatic Rectification of Long Image Sequences. In: Asian Conference on Computer Vision, (2004)
15. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press (2000)
16. Blackman, S., Popoli, R.: Design and Analysis of Modern Tracking Systems. Artech House, Norwood (1999)
17. Bertsekas, D.: Linear Network Optimization: Algorithms and Codes. The MIT Press, Cambridge (1991)
18. Comaniciu, D., Ramesh, V., Meer, P.: Real-time tracking of non-rigid objects using mean shift, In: International Conference on Computer Vision and Pattern Recognition, (2000) 2142-2149
19. Cheng, Y.: Mean Shift, Mode Seeking, and Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(8) (1995) 790-799
20. Comaniciu, D., Meer, P.: Mean Shift: A Robust Approach Toward Feature Space Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5) (2002) 603-619