Abstract
This paper proposes a novel algorithm for individual recognition by gait. The method of Procrustes shape analysis is used to produce Procrustes Mean Shape (PMS) as a compressed representation of gait sequence. PMS is adopted as the gait signature in this paper. Instead of using the Procrustes mean shape distance as a similarity measure, we introduce shape context descriptor to measure the similarity between two PMSs. Shape context describes a distribution of all boundary points on a shape with respect to any single boundary point by a histogram of log-polar plot, and offers us a global discriminative characterization of the shape. Standard pattern recognition techniques are used to classify different patterns. The experiments on CASIA Gait Database demonstrate that the proposed method outperforms other algorithms in both classification performance and verification performance.
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References
Bhanu, B., Han, J.: Individual Recognition by Kinematic-based Gait Analysis. In: 16th International Conference on Pattern Recognition, pp. 343–346. IEEE Computer Society, Quebec (2002)
Lee, L., Grimson, W.E.L.: Gait Analysis for Recognition and Classification. In: International Conference on Automatic Face and Gesture Recognition, pp. 148–155. IEEE Computer Society, Washington (2002)
Sarkar, S., Phillips, P.J., Liu, Z., Vega, I.R., Grother, P., Bowyer, K.W.: The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 27, 162–177 (2005)
Han, J., Bhanu, B.: Individual Recognition Using Gait Energy Image. IEEE Trans. Pattern Anal. Mach. Intell. 28, 316–322 (2006)
Wang, L., Tan, T., Hu, W., Ning, H.: Automatic Gait Recognition Based on Statistical Shape Analysis. IEEE Trans. Image Process. 12, 1120–1131 (2003)
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24, 509–522 (2002)
CASIA Gait Database, http://www.sinobiometrics.com
Veltkamp, R.C., Latecki, L.J.: Properties and Performance of Shape Similarity Measures. In: IFCS 2006 Conference: Data Science and Classification, pp. 47–56. Springer, Berlin (2006)
Kent, J.T.: New Directions in Shape Analysis. Art of Statistical Science: A Tribute to G. S. Watson, pp. 115–127. Wiley, New York (1992)
Papadimitriou, C.H., Steiglitz, K.: Combinatorial optimization: algorithms and complexity. Prentice-Hall, Englewood Cliffs (1982)
Jonker, J., Volgenant, A.: A Shortest Augmenting Path Algorithm for Dense and Sparse Linear Assignment Problems. Computing 38, 325–440 (1987)
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face Recognition Algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1090–1104 (2000)
BenAbdelkader, C., Cutler, R., Davis, L.: Motion-based recognition of people in EigenGait space. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 267–272. IEEE Computer Society, Washington (2002)
Chen, S., Ma, T., Huang, W., Gao, Y.: Gait Recognition Based on Shape Context Descriptor (in Chinese). Chinese journal of Pattern Recognition and Artificial Intelligence 20, 794–799 (2007)
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Zhang, Y., Yang, N., Li, W., Wu, X., Ruan, Q. (2010). Gait Recognition Using Procrustes Shape Analysis and Shape Context. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12297-2_25
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DOI: https://doi.org/10.1007/978-3-642-12297-2_25
Publisher Name: Springer, Berlin, Heidelberg
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