Face recognition via statistical codebook modeling and matching

Author

Jing-Ying Hsu ; Chih-Hong Chu ; Shu-Chen Li ; Jie-Ci Yang

Author_Institution

Adv. Technol. Center, Wistron Corp., Taipei, Taiwan

fYear

2013

fDate

1-4 Oct. 2013

Firstpage

72

Lastpage

73

Abstract

This paper presents a novel face recognition method to reduce the influence form varying face postures while maintaining high computational efficiency. Via building a codebook of an ASM face model and adopting the Mann-Whitney U-test matching method, the input face can be compared with the database much efficiently and effectively. Experimental results show that the proposed method has better recognition result and less computational complexity, and is competitive and practical for implementing into the smart equipments.

Keywords

computational complexity; face recognition; image coding; statistical analysis; ASM face model; Mann-Whitney U-test matching method; computational complexity; computational efficiency; face postures; face recognition; smart equipments; statistical codebook matching; statistical codebook modeling; Active shape model; Computational complexity; Computational modeling; Conferences; Databases; Face; Face recognition; Active Shape Model; Face Recognition; MannWhitney U-test; VQH Codebook;

fLanguage

English

Publisher

ieee

Conference_Titel

Consumer Electronics (GCCE), 2013 IEEE 2nd Global Conference on

Conference_Location

Tokyo

Print_ISBN

978-1-4799-0890-5

Type

conf

DOI

10.1109/GCCE.2013.6664928

Filename

6664928