Title: Improvement of a face recognition method for high jumper with a single sample based on Lucas-Kanade algorithm

Authors: Guoxing Shi

Addresses: Wuxi Institute of Technology, Wuxi, Jiangsu, 214000, China

Abstract: In order to improve the identification accuracy of a dynamic single sample, a face recognition method based on Lucas-Kanade algorithm is proposed. The weighted Lucas-Kanade (LK) algorithm is used to obtain the single-sample affine transformation parameters of the high jumper's side face block and the corresponding front face block, and the optimal parameters of face pose correction are found through the maximum Gabor similarity, the method of face recognition for high jumper with a single sample is completed. Simulation results show that both the front face recognition rate and side-face recognition rate of the proposed method can reach more than 95% and the face recognition recall rate of the proposed method ranges from 90% to 100%. Compared with the traditional method, the recall rate has been significantly improved. In addition, when there are 440 face images, the recognition time is 1,177 ms, which is shorter than the traditional method.

Keywords: Lucas-Kanade algorithm; high jumper with a single sample; face recognition method; improvement.

DOI: 10.1504/IJBM.2021.114655

International Journal of Biometrics, 2021 Vol.13 No.2/3, pp.258 - 271

Received: 24 Apr 2020
Accepted: 11 Aug 2020
Published online: 29 Apr 2021 *

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