NDLI: A VQ-based fast face recognition algorithm using optimized codebook

Content Provider	IEEE Xplore Digital Library
Author	Qiu Chen Kotani, K. Fei-Fei Lee Ohmi, T.
Copyright Year	2008
Description	Author affiliation: New Ind. Creation Hatchery Center, Tohoku Univ., Sendai (Qiu Chen; Fei-Fei Lee; Ohmi, T.)
Abstract	In this paper, we present a VQ-based fast face recognition algorithm using an optimized codebook. Previously, Chen et al. [2006] proposed a novel codebook design method based on the systematic classification and organization of code patterns abstracted from facial images for reliable face recognition. In this paper, an improved codebook design method is proposed. Combined by a systematically organized codebook based on the classification of code patterns and another codebook created by Kohonenpsilas Self-Organizing Maps (SOM), an optimized codebook consisted of 2times2 codevectors for facial images is generated. We demonstrate the performance of our algorithm using publicly available AT&T database containing variations in lighting, posing, and expressions. Compared with the algorithms employing original codebook or SOM codebook separately, experimental results show face recognition using the optimized codebook is more efficient. The highest average recognition rate of 98.2% is obtained for 40 personspsila 400 images of AT&T database. A table look-up (TLU) method is also proposed for the speed up of the recognition processing in this paper. By applying this method in the quantization step, the total recognition processing time achieves only 28 msec, enabling real-time face recognition.
Starting Page	298
Ending Page	303
File Size	372931
Page Count	6
File Format	PDF
ISBN	9781424422388
DOI	10.1109/ICWAPR.2008.4635793
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis SOM Histograms Codebook Databases Face recognition Design methodology Vector quantization Pattern classification Classification algorithms Face
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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