Analysis of Spatio-Temporal Dynamic Patterns of Gait for Recognition

SONIA, DAS and SUKADEV, MEHER and UPENDRA, KUMAR SAHOO (2017) Analysis of Spatio-Temporal Dynamic Patterns of Gait for Recognition. In: Seventh International Conference on Advances in Computing, Control and Networking - ACCN 2017, 23-24 September 2017, Bangkok, Thailand.

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This work presents a five-phase automatic gait recognition method that analyzes the spatiotemporal shape and dynamic motion (STS-DM) characteristics of a human subject's silhouette to identify the subject in the presence of many challenging factors that affect gait. Phase-1 describes Krawtchouk Moments for feature extraction; phase-2 describes phase weighted magnitude spectra of the Fourier descriptor of a silhouette. Phase-3 gives a full body shape and motion analysis using ellipses. In Phase-4, dynamic time warping is used to analyze thigh angle rotation pattern. In phase-5 DHT based height varying signal pattern is analyzed. Five phases are fused to give a robust identification system.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Krawtchouk Moments; STS-DM;DTW; DHT
Depositing User: Mr. John Steve
Date Deposited: 10 Mar 2019 12:00
Last Modified: 10 Mar 2019 12:00

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