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Title: Analysis of Spatio-Temporal Dynamic Patterns of Gait for Recognition
Authors: Das, Sonia
Meher, Sukadev
Keywords: Krawtchouk Moments
Issue Date: Sep-2017
Citation: Seventh International Conference on Advances in Computing, Control and Networking (ACCN-2017), Bangkok, Thailand, 23-24 September, 2017.
Abstract: 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.
Description: Copyright of this document belongs to proceedings publisher.
Appears in Collections:Conference Papers

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