Abstract
In recent years, many gait recognition algorithms have been developed, but most of them depend on a specific view angle. However, view angle variation is a significant factor among those that affect gait recognition performance. It is important to find the relationship between the performance and the view angle. In this paper, we discuss the effect of view angle variation on appearance-based gait recognition performance. A multi-view gait database (124 subjects and 11 view directions) is created for our research. We propose two models, a geometrical one and a mathematical one, to model the effect of view angle variation on appearance-based gait recognition. These models will be valuable for designing robust gait recognition systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Murray, M.P.: Gait as a total pattern of movement. American Journal of Physical Medicine 46(1), 290–332 (1967)
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 Transactions on Pattern Analysis and Machine Intelligence 27(2), 162–177 (2005)
Johnson, A.Y., Bobick, A.F.: A multi-view method for gait recognition using static body parameters. In: Proc. of 3rd International Conference on Audio and Video Based Biometric Person Authentication, pp. 301–311 (2001)
Kale, A., Chowdhury, A.K.R., Chellappa, R.: Towards a view invariant gait recognition algorithm. In: Proc. of IEEE Conference on Advanced Video and Signal Based Surveillance, FL, USA, pp. 143–150 (2003)
Shutler, J.D., Grant, M.G., Nixon, M.S., Carter, J.N.: On a large sequence-based human gait database. In: Proc. of the 4th International Conference on Recent Advances in Soft Computing, pp. 66–72 (2002)
Center for biometrics and security research, casia, http://www.cbsr.ia.ac.cn
Han, J., Bhanu, B.: Statistical feature fusion for gait-based human recognition. In: Proc. of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington DC, USA, pp. II842–II847 (2004)
Yu, S., Wang, L., Hu, W., Tan, T.: Gait analysis for human identification in frequency domain. In: Proc. of the 3rd International Conference on Image and Graphics, Hong Kong, China, pp. 282–285 (2004)
Wang, L., Tan, T., Ning, H., Hu, W.: Silhouette analysis-based gait recognition for human identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1505–1518 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, S., Tan, D., Tan, T. (2006). Modelling the Effect of View Angle Variation on Appearance-Based Gait Recognition. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_81
Download citation
DOI: https://doi.org/10.1007/11612032_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
eBook Packages: Computer ScienceComputer Science (R0)