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• W2187979236 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." @default.
• W2187979236 created "2016-06-24" @default.
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• W2187979236 date "2015-01-01" @default.
• W2187979236 modified "2023-09-26" @default.
• W2187979236 title "A New Gait-Based Identification Method Using Local Gauss Maps" @default.
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• W2187979236 doi "https://doi.org/10.1007/978-3-319-16628-5_1" @default.
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