Occlusion detection and gait silhouette reconstruction from degraded scenes

Signal, Image and Video Processing

Volumn 5, Issue 4, 2011, Pages 415-430

  Roy, Aditi ^a   Sural, Shamik ^a   Mukherjee, Jayanta ^a   Rigoll, Gerhard ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

BGPDM; Dynamic programming; Gait; Occlusion; Pose detection; Silhouette reconstruction

Indexed keywords

BGPDM; GAIT; OCCLUSION; POSE DETECTION; SILHOUETTE RECONSTRUCTION;

BIOMETRICS;

DYNAMIC PROGRAMMING;

EID: 80255141906     PISSN: 18631703     EISSN: 18631711     Source Type: Journal    
DOI: 10.1007/s11760-011-0245-5     Document Type: Article

References (39)

1. Larsen P. K., Simonsen E. B., Lynnerup N.: Gait analysis in forensic medicine. J. Forensic Sci. 53(5), 1149-1153 (2008).
2. Cunado D., Nixon M. S., Carter J. N.: Automatic extraction and description of human gait models for recognition purposes. Proc. CVIU 90(1), 1-41 (2003).
3. Bobick, A., Johnson, A.: Gait recognition using static, activity-specific parameters In: Proceedings of the IEEE Conference on CVPR, vol. 1, pp. 423-430 (2001).
4. Yam C., Nixon M. S., Carter J. N.: Automated person recognition by walking and running via model-based approaches. Pattern Recognit. 37(5), 1057-1072 (2004).
5. Jain, A., Dube, T., Ghosh, D.: A fuzzy approach to person identification using gait. In: Proceedings of the IET International Conference on Visual Information Engineering (VIE), pp. 174-179 (2006).
6. Zhang R., Vogler C., Metaxas D.: Human gait recognition at sagittal plane. Image Vis. Comput. 25(3), 321-330 (2007).
7. Lu, H., Plataniotis, K. N., Venetsanopoulos, A. N.: A full-body layered deformable model for automatic model-based gait recognition. EURASIP J. Adv. Signal Process. 2008(Article ID 261317) (2008). doi: 10. 1155/2008/261317.
8. Huang, X., Boulgouris, N. V. Model-based human gait recognition using fusion of features. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 0, pp. 1469-1472 (2009).
9. Kale A., Sundaresan A., Rajagopalan A. N., Cuntoor N. P., Roy-Chowdhury A. K., Kruger V., Chellappa R.: Identification of humans using gait. IEEE Trans. Image Process. 13, 1163-1173 (2004).
10. Kale, A., Rajagopalan, A., Cuntoor, N., Krueger, V.: Gait-based recognition of humans using continuous HMMs. In: Proceedings of the International Conference on Automatic Face and Gesture Recognition, pp. 321-326 (2002).
11. Chen C. H., Liang J., Zhao H., Hu H., Tian J.: Factorial HMM and parallel HMM for gait recognition. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 39(1), 114-123 (2009).
12. Sundaresan, A., Roy-Chowdhury, A. K., Chellappa, R.: A hidden markov model based framework for recognition of humans frem gait sequences. In: Proceedings of the IEEE Conference Image Processing, vol. 2, pp. 93-99 (2003).
13. Niyogi, S. A., Adelson, E. H.: Analyzing and recognizing walking figures in XYT. In: Proceedings of the CVPR, pp. 469-474 (1994).
14. Little J., Boyd J.: Recognizing people by their gait: the shape of motion. Videre J. Comput. Vis. Res. 1(2), 1-32 (1998).
15. BenAbdelkader, C., Cutler, R., Davis, L.: Motion-based recognition of people in eigengait space. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, pp. 267-274 (2002).
16. Vega, I., Sarkar, S.: Experiments on gait analysis by exploiting nonstationarity in the distribution of feature relationships. In: Proceedings of the International Conference on Pattern Recognition, vol. 1, pp. 1-4 (2002).
17. Sarkar S., Phillips P. J., Liu Z., Robledo-Vega I., Grother P., Bowyer K. W.: The human ID gait challenge problem: data sets, performance, and analysis. IEEE Trans. Pattern Anal. Mach. Intel. 27(2), 162-177 (2005).
18. Hayfron-Acquah, J., Nixon, M., Carter, J.: Human identification by spatio-temporal symmetry. In: Proceedings of the International Conference on Pattern Recognition, vol. 1, pp. 632-635 (2002).
19. Lee L., Grimson, W.: Gait analysis for recognition and classification. In: Proceedings of the International Conference on Automatic Face and Gesture Recognition, pp. 155-162 (2002).
20. Boulgouris N. V., Hatzinakos D., Plataniotis K. N.: Gait recognition: a challenging signal processing technology for biometrics identification. IEEE Signal Process. Mag. 22(6), 78-90 (2005).
21. Lu J., Zhang E.: Gait recognition for human identification based on ICA and fuzzy SVM through multiple views fusion. Pattern Recognit. Lett. 28, 2401-2411 (2007).
22. Nixon, M. S., Carter, J. N.: Advances in automatic gait recognition. In: Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition, pp. 139-144 (2004).
23. Han J., Bhanu B.: Individual recognition using gait energy image. IEEE Trans. Pattern Anal. Mach. Intel. 28(2), 316-322 (2006).
24. Yanga X., Zhoua Y., Zhanga T., Shua G., Yanga J.: Gait recognition based on dynamic region analysis. Signal Process. 88(9), 2350-2356 (2008).
25. Chen C., Liang J., Hu H., Tian J.: Frame difference energy image for gait recognition with incomplete silhouettes. Pattern Recognit. Lett. 30(11), 977-984 (2009).
26. Zhanga E., Zhao Y., Xionga W.: Energy image plus 2DLPP for gait recognition. Signal Process. 90(7), 2295-2302 (2010).
27. Pullen, K., Bregler, C.: Motion capture assisted animation: texturing and synthesis. In: Proceedings of theof SIGGRAPH, pp. 501-508 (2002).
28. Wang J. M., Fleet D. J., Hertzmann A.: Gaussian process dynamical models for human motion. IEEE Trans. PAMI 30(2), 283-298 (2008).
29. Lawrence, N. D.(2004) Gaussian process latent variable models for visualisation of high dimensional data. In: Thrun, S., Saul, L., Schlkopf, B. (eds.). Advances in Neural Information Processing Systems, pp. 329-336 MIT Press, Cambridge, MA.
30. Rabiner L. R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257-286 (1989).
31. Wang, J. M., Fleet, D. J., Hertzmann, A.: Gaussian process dynamical models. In: Proceedings of the NIPS, pp. 1441-1448 (2005).
32. Urtasun, R., Fleet, D. J., Fua, P.: 3D people tracking with Gaussian process dynamical models. In: Proceedings of the CVPR, pp. 238-245 (2006).
33. Gross, R., Shi, J.: The CMU Motion of Body (MoBo) Database. Technical report CMU-RI-TR-01-18, Robotics Institute, Carnegie Mellon University (2001).
34. Center for biometrics and security research, CASIA. http://www. cbsr. ia. ac. cn.
35. Turk M., Pentland A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71-86 (1991).
36. Hofmann, M., Sural, S., Rigoll, G.: Gait recognition in the presence of occlusion: a new dataset and baseline algorithms. In: Proceedings of the International Conference on Computer Graphics, Visualization and Computer Vision (WSCG). Plzen, Czech Republic (2011).
37. http://www. mmk. ei. tum. de/~hom/tumiit/tumiitgait. html.
38. Staufferand, C., Grimson, W. E. L.: Adaptive background mixture modelsfor real-time tracking. In: Proceedings of the CVPR, pp. 246-252 (1999).
39. Tanimoto, T. T.: IBM Internal Report, 17 Nov (1957).