Identity Recognition Algorithm Using Improved Gabor Feature Selection of Gait Energy Image

2016 International Conference on Communication, Image and Signal Processing

物理学;无线电电子学;计算机科学

Chao, Liang^1 ; Ling-Yao, J.I.A.^1 ; Dong-Cheng, S.H.I.^1

School of Computer Science and Engineering, Changchun University of Technology, Changchun

130012, China^1

关键词: Gait database;    Gait energy images;    Gait recognition;    Identity recognition;    Kernel Fisher;    Kernel matrices;    Nearest Neighbor classifier;    Recognition accuracy;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/787/1/012015/pdf
DOI  :  10.1088/1742-6596/787/1/012015

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

This paper describes an effective gait recognition approach based on Gabor features of gait energy image. In this paper, the kernel Fisher analysis combined with kernel matrix is proposed to select dominant features. The nearest neighbor classifier based on whitened cosine distance is used to discriminate different gait patterns. The approach proposed is tested on the CASIA and USF gait databases. The results show that our approach outperforms other state of gait recognition approaches in terms of recognition accuracy and robustness.