Gait recognition based on Procrustes mean shape and Fan-Beam transform

Xiaoxue Sun; Wenxiu Sui; Guoren Gao

doi:10.1117/12.3045415

9 October 2024 Gait recognition based on Procrustes mean shape and Fan-Beam transform

Xiaoxue Sun, Wenxiu Sui, Guoren Gao

Proceedings Volume 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024); 132880M (2024) https://doi.org/10.1117/12.3045415
Event: Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 2024, Chengdu, China

Abstract

To address the limitations of gait recognition based on a single feature, complementary dynamic and static information is integrated for more accurate identification. Initially, Procrustes mean shape is utilized to extract static features of gait silhouette contours. Then, gait energy image (GEI) is computed, followed by Fan-Beam transformation of GEI. Twodimensional principal component analysis is employed for feature space dimensionality reduction to obtain frequency dynamic features of the moving target. Finally, the Euclidean distances of the two features are fused to achieve the ultimate recognition outcome. Experimental verification on Dataset B from the Chinese Academy of Sciences demonstrates the expected recognition performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoxue Sun, Wenxiu Sui, and Guoren Gao "Gait recognition based on Procrustes mean shape and Fan-Beam transform", Proc. SPIE 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 132880M (9 October 2024); https://doi.org/10.1117/12.3045415

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