A new gait-based identification method using local gauss maps

9Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We propose a new descriptor for human identification based on gait. The current and most prevailing trend in gait representation revolves around encoding body shapes as silhouettes averaged over gait cycles. Our method, however, captures geometric properties of the silhouettes boundaries. Namely, we evaluate contour curvatures locally using Gauss maps. This results in an improved shape representation, as contrasted to average silhouettes. In addition, our approach does not require prior training. We thoroughly demonstrate the superiority of our method in gait-based human identification compared to state-of-the-art approaches. We use the OU-ISIR Large Population dataset, with over 4000 subjects captured at different viewing angles, to provide statistically reliable results.

Cite

CITATION STYLE

APA

El-Alfy, H., Mitsugami, I., & Yagi, Y. (2015). A new gait-based identification method using local gauss maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9008, pp. 3–18). Springer Verlag. https://doi.org/10.1007/978-3-319-16628-5_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free