Abstract
This paper describes a new method to track people walking by matching their gait image sequences in the frequency domain. When a person walks at a distance from a camera, that person often appears and disappears due to being occluded by other people and/or objects, or by going out of the field of view. Therefore, it is important to track the person by taking correspondence of the image sequences between before and after the disappearance. In the case of tracking, the computational time is more crucial factor than that in the case of identification. We create a three-dimensional volume by piling up an image sequence of human walking. After using Fourier analysis to extract the frequency characteristics of the volume, our method computes the similarity of two volumes. We propose a method to compute their correlation of the amplitude of the principal frequencies to improve the cost of comparison. Finally, we experimentally test our method and validate that the amplitude of principal frequencies and spatial information are important to discriminate gait image sequences.
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.
Similar content being viewed by others
References
Yam, C., Nixon, M., Carter, J.: Automated person recognition by walking and running via model-based approaches. Pattern Recognition 37, 1057–1072 (2004)
Cunado, D., Nixon, M., Carter, J.: Automatic extraction and description of human gait models for recognition purposes. Computer Vision and Image Understanding 90, 1–41 (2003)
Urtasun, R., Fua, P.: 3d tracking for gait characterization and recognition. In: Proc. Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 17–22 (2004)
Bobick, A., Johnson, A.: Gait recognition using static activity-specific parameters. In: Proc. Computer Vision and Pattern Recognition (2001)
Lee, L., Grimson, W.: Gait analysis for recognition and classification. In: Proc. Fifth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 155–162 (2002)
Niyogi, S., Adelson, E.: Analyzing and recognizing walking figures in xyt. In: Proc. Computer Vision and Pattern Recognition, pp. 469–474 (1994)
Murase, H., Sakai, R.: Moving object recognition in eigenspace representation: gait analysis and lip reading. Pattern Recognition Letters 17, 155–162 (1996)
Little, J., Boyd, J.: Recognizing people by their gait: The shape of motion. Videre 1 (1998)
Liu, F., Picard, R.: Finding periodicity in space and time. In: Proc. the Sixth International Conference on Computer Vision, pp. 376–383 (1998)
BenAbdelkader, C., Culter, R., Nanda, H., Davis, L.: Eigengait: Motion-based recognition people using image self-similarity. In: Proc. AVBPA (2001)
Liu, Y., Collins, R., Tsin, Y.: Gait sequence analysis using frieze patterns. In: Proc. the 7th European Conference on Computer Vision, vol. 2, pp. 657–671 (2002)
Sarkar, S., Phillips, P., Liu, Z., Vega, I., Grother, P., Bowyer, K.: The humanid gait challenge problem: Data sets, performance, and analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 162–177 (2005)
Han, J., Bhanu, B.: Statistical feature fusion for gait-based human recognition. In: Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 842–847 (2004)
Ohara, Y., Sagawa, R., Echigo, T., Yagi, Y.: Gait volume: Spatio-temporal analysis of walking. In: Proc. The fifth Workshop on Omnidirectional Vision, Camera Networks and Non-classical cameras (OMNIVIS 2004), Prague, Czech (2004)
Mituyosi, T., Yagi, Y., Yachida, M.: Real-time human feature acquisition and human tracking by omnidirectional image sensor. In: Proc. IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems, pp. 258–263 (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
Sagawa, R., Makihara, Y., Echigo, T., Yagi, Y. (2006). Matching Gait Image Sequences in the Frequency Domain for Tracking People at a Distance. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612704_15
Download citation
DOI: https://doi.org/10.1007/11612704_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31244-4
Online ISBN: 978-3-540-32432-4
eBook Packages: Computer ScienceComputer Science (R0)