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Robust gait recognition from extremely low frame-rate videos
conference contribution
posted on 2013-01-01, 00:00 authored by Y Guan, Chang-Tsun LiChang-Tsun Li, S D ChoudhuryIn this paper, we propose a gait recognition method for extremely low frame-rate videos. Different from the popular temporal reconstruction-based methods, the proposed method uses the average gait over the whole sequence as input feature template. Assuming the effect caused by extremely low frame-rate or large gait fluctuations are intra-class variations that the gallery data fails to capture, we build a general model based on random subspace method. More specifically, a number of weak classifiers are combined to reduce the generalization errors. We evaluate our method on the OU-ISIR-D dataset with large/small gait fluctuations, and very competitive results are achieved when both the probe and gallery are extremely low frame-rate gait sequences (e.g., 1 fps).
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Event
International Association for Pattern Recognition. International Workshop (2013 : Lisbon, Portugal)Series
International Association for Pattern Recognition International WorkshopPagination
1 - 4Publisher
Institute of Electrical and Electronics EngineersLocation
Lisbon, PortugalPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2013-04-04End date
2013-04-05ISBN-13
9781467349895Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2013, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
IWBF 2013 : Proceedings of the 2013 International Workshop on Biometrics and ForensicsUsage metrics
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