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2018 | OriginalPaper | Buchkapitel

Gait Recognition Using Motion Trajectory Analysis

verfasst von : Muhammad Hassan Khan, Frederic Li, Muhammad Shahid Farid, Marcin Grzegorzek

Erschienen in: Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017

Verlag: Springer International Publishing

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Abstract

Gait recognition has received significant attention in the recent years due to its applications in numerous fields of computer vision, particularly in automated person identification in visual surveillance and monitoring systems. In this paper, we propose a novel algorithm for gait recognition using spatio-temporal motion characteristics of a person. The proposed algorithm consists of four steps. First, motion features are extracted from video sequence which are used to generate a codebook in the second step. In a third step, the local descriptors are encoded using Fisher vector encoding. Finally, the encoded features are classified using linear Support Vector Machine (SVM). The performance of the proposed algorithm is evaluated and compared with state-of-the-art on two widely used gait databases TUM GAID and CASIA-A. The recognition results demonstrate the effectiveness of the proposed algorithm.

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Vorheriges Kapitel Diagnostic Rule Extraction Using the Dempster-Shafer Theory Extended for Fuzzy Focal Elements

Nächstes Kapitel Methodology of the Construction of a GDPLL(k) Grammar-Based Syntactic Pattern Recognition System

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Titel: Gait Recognition Using Motion Trajectory Analysis
verfasst von: Muhammad Hassan Khan
Frederic Li
Muhammad Shahid Farid
Marcin Grzegorzek
Verlag: Springer International Publishing
Buch: Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017
Print ISBN: 978-3-319-59161-2

Electronic ISBN: 978-3-319-59162-9

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-59162-9_8

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