Real-time hand tracking using a mean shift embedded particle filter

Pattern Recognition

Volumn 40, Issue 7, 2007, Pages 1958-1970

  Shan, Caifeng ^a   Tan, Tieniu ^b   Wei, Yucheng ^b  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

Hand gesture recognition; Hand tracking; Human computer interaction; Mean shift; Particle filter

Indexed keywords

ALGORITHMS; GESTURE RECOGNITION; HUMAN COMPUTER INTERACTION; INTERFACES (COMPUTER); WHEELCHAIRS;

HAND GESTURE RECOGNITION; HAND TRACKING; MEAN SHIFT; PARTICLE FILTERS;

TRACKING (POSITION);

EID: 33947630354     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2006.12.012     Document Type: Article

References (50)

1. Y. Wu, Vision and learning for intelligent human-computer interaction, Ph.D. Thesis, University of Illinois at Urbana-Champaign, 2001.
2. Pavlovic V., Sharma R., and Huang T. Visual interpretation of hand gestures for human-computer interaction: a review. IEEE Trans. Pattern Anal. Mach. Intell. 19 7 (1997) 677-695
3. McAllister G., McKenna S., and Ricketts I. Hand tracking for behaviour understanding. Image Vision Comput. 20 12 (2002) 827-840
4. K. Oka, Y. Sato, H. Koike, Real-time tracking of multiple fingertips and gesture recognition for augmented desk interface systems, in: Proceedings of IEEE International Conference on Automated Face and Gesture Recognition (FG'02), 2002, pp. 411-416.
5. I. Laptev, T. Lindeberg, Tracking of multi-state hand models using particle filtering and a hierarchy of multi-scale image features, in: Proceedings of IEEE Workshop on Scale-Space and Morphology, 2001.
6. H. Fei, I. Reid, Probabilistic tracking and recognition of non-rigid hand motion, in: Proceedings of IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG'03), 2003, pp. 60-67.
7. S. Lu, D. Metaxas, D. Samaras, J. Oliensis, Using multiple cues for hand tracking and model refinement, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'03), 2003, pp. II: 443-450.
8. H. Zhou, T. Huang, Tracking articulated hand motion with eigen dynamics analysis in: Proceedings of IEEE International Conference on Computer Vision (ICCV'03), 2003, pp. 1102-1109.
9. Tsap L. Gesture-tracking in real time with dynamic regional range computation. Real Time Imaging 8 2 (2002) 115-126
10. A. Shamaie, A. Sutherland, A dynamic model for real-time tracking of hands in bimanual movements, Gesture-Based Communication in Human-Computer Interaction (International Gesture Workshop, GW03).
11. E.B. Sudderth, M.I. Mandel, W.T. Freeman, A.S. Willsky, Visual hand tracking using nonparametric belief propagation, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04), 2004.
12. M. Kolsch, M. Turk, Fast 2d hand tracking with flocks of features and multi-cue integration, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04), 2004.
13. Q. Yuan, S. Sclaroff, V. Athitsos, Automatic 2d hand tracking in video sequences in: Proceedings of IEEE Workshop on Applications of Computer Vision (WACV'05), 2005.
14. Inaguma T., Saji H., and Nakatani H. Hand motion tracking based on a constraint of three-dimensional continuity. J. Electron. Imaging 14 1 (2005) 013021
15. W.Y. Chang, C.S. Chen, Y.P. Hung, Appearance-guided particle filtering for articulated hand tracking, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
16. Wu S., and Hong L. Hand tracking in a natural conversational environment by the interacting multiple model and probabilistic data association (imm-pda) algorithm. Pattern Recognition 38 (2005) 2143-2158
17. Stenger B., Thayananthan A., Torr P.H.S., and Cipolla R. Model-based hand tracking using a hierarchical Bayesian filter. IEEE Trans. Pattern Anal. Mach. Intell. 28 9 (2006) 1372-1384
18. Isard M., and Blake A. Condensation-conditional density propagation for visual tracking. Int. J. Comput. Vision 29 1 (1998) 5-28
19. Ng C., and Ranganath S. Real-time gesture recognition system and application. Image Vision Comput. 20 13-14 (2002) 993-1007
20. M. Isard, A. Blake, ICONDENSATION: unifying low-level tracking in a stochastic framework, in: Proceedings of European Conference on Computer Vision (ECCV'98), vol. 1, Freiburg, Germany, 1998, pp. 893-908.
21. Yang M., Ahuja N., and Tabb M. Extraction of 2d motion trajectories and its application to hand gesture recognition. IEEE Trans. Pattern Anal. Mach. Intell. 24 8 (2002) 1061-1074
22. Vision based hand gesture recognition systems. URL 〈http://ls7-www.cs.uni-dortmund.de/research/gesture/vbgr-table.html〉.
23. M. Bray, E. Koller-Meier, L. Van Gool, Smart particle filtering for 3d hand tracking, in: Proceedings of IEEE International Conference on Automated Face and Gesture Recognition (FG'04), 2004, pp. 675-680.
24. Arulampalam M., Maskell S., Gordon N., and Clapp T. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans. Signal Process. 50 2 (2002) 174-189
25. Y. Rui, Y. Chen, Better proposal distributions: object tracking using the unscented particle filter, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'01), vol. 2, Hawaii, 2001, pp. 786-793.
26. J. MacCormick, M. Isard, Partitioned sampling, articulated objects, and interface-quality hand tracking, in: Proceedings of European Conference on Computer Vision (ECCV'00), 2000, pp. 3-19.
27. T. Cham, J.M. Rehg, A multiple hypothesis approach to figure tracking, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'99), 1999, pp. 239-245.
28. J. Deutscher, A. Blake, I. Reid, Articulated body motion capture by annealled particle filtering, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'00), 2000, pp. 126-133.
29. K. Choo, D.J. Fleet, People tracking using hybrid Monte Carlo filtering, in: Proceedings of IEEE International Conference on Computer Vision (ICCV'01), 2001, pp. 1068-1075.
30. C. Chang, R. Ansari, Kernel particle filter: iterative sampling for efficient visual tracking, in: Proceedings of IEEE International Conference on Image Processing (ICIP'03), 2003.
31. B. Han, D. Comaniciu, Y. Zhu, L. Davis, Incremental density approximation and kernel-based Bayesian filtering for object tracking, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'04), Washington, DC, 2004.
32. D. Comaniciu, V. Ramesh, P. Meer, Real-time tracking of non-rigid objects using mean shift, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'00), South Carolina, 2000, pp. 142-149.
33. C. Shan, Y. Wei, T. Tan, F. Ojardias, Real time hand tracking by combining particle filtering and mean shift, in: Proceedings of IEEE International Conference on Automated Face and Gesture Recognition (FG'04), Seoul, Korea, 2004, pp. 669-674.
34. P. Perez, C. Hue, J. Vermaak, M. Gangnet, Color-based probabilistic tracking, in: Proceedings of European Conference on Computer Vision (ECCV'02), 2002, pp. I: 661-675.
35. Nummiaro K., Koller-Meier E., and Van Gool L. An adaptive color-based particle filter. Image Vision Comput. 21 1 (2003) 99-110
36. G. Bradski, Computer vision face tracking for use in a perceptual user interface, Intel Technol. J. Q2.
37. D. Comaniciu, V. Ramesh, Mean shift and optimal prediction for efficient object tracking, in: Proceedings of IEEE Conference on Image Processing (ICIP'00), Vancouver, Canada, 2000, pp. 70-73.
38. C. Yang, R. Duraiswami, L. Davis, Efficient mean-shift tracking via a new similarity measure, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
39. Blake A., and Isard M. Active Contours (1998), Springer, Berlin
40. M. Soriano, B. Martinkauppi, S. Huovinen, M. Laaksonen, Skin detection in video under changing illumination conditions, in: Proceedings of International Conference on Pattern Recognition (ICPR'00), 2000, pp. 839-842.
41. H.P. Graf, E. Cosatto, D. Gibbon, M. Kocheisen, E. Petajan, Multi-modal system for locating heads and faces, in: Proceedings of International Conference on Automatic Face and Gesture Recognition (FG'96), 1996, pp. 88-93.
42. Starner T., Weaver J., and Pentland A. Real-time american sign language recognition using desk and wearable computer based video. IEEE Trans. Pattern Anal. Mach. Intell. 20 12 (1998) 1371-1375
43. M.J. Black, A.D. Jepson, Recognition temporal trajectories using the CONDENSATION algorithm, in: Proceedings of IEEE International Conference on Automated Face and Gesture Recognition (FG'98), Japan, 1998, pp. 16-21.
44. Psarrou A., Gong S., and Walter M. Recognition of human gestures and behaviour based on motion trajectories. Image Vision Comput. 20 5-6 (2002) 349-358
45. Bobick A., and Davis J. The recognition of human movement using temporal templates. IEEE Trans. Pattern Anal. Mach. Intell. 23 3 (2001) 257-267
46. Y. Boers, On the number of samples to be drawn in particle filtering, in: IEE Colloquium on Target Tracking: Algorithms and Applications, 1999, pp. 5/1-5/6.
47. D. Koeller, R. Fratkina, Using learning for approximation in stochastic processes, in: Proceedings of International Conference on Machine Learning (ICML'98), 1998.
48. D. Fox, W. Burgard, F. Dellaert, S. Thrun, Monte Carlo localization: efficient position estimation for mobile robots, in: Proceedings of National Conference on Artificial Intelligence (AAAI), 1999.
49. D. Fox, Kld-sampling: adaptive particle filters, in: Advances in Neural Information Processing Systems (NIPS), 2001.
50. A. Soto, Self adaptive particle filter, in: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI'05), 2005.