Citation

Neo, Han Foon and Teo, Chuan Chin and Teoh, Andrew Beng Jin (2007) A Study on Optimal Face Ratio for Recognition Using Part-based Feature Extractor. In: 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, 16-18 Dec. 2007, Shanghai, China.

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Abstract

This paper aims to investigate the optimal face ratio for recognition. Face data are normalized to several ratios, which are 25%, 50% (equivalent to right and left face), and 75% of the full-face. The advantages of using different face ratios are these face data reduce the amount of computational power and storage requirements significantly. For fair comparison, various part-based linear subspace feature extractors, namely Non-negative matrix factorization (NMF), Local NMF (LNMF) and Spatially Confined NMF (SFNMF) are used to estimate the optimal face ratio. Our results show that 75% faces are good enough to produce demonstrably recognition accuracy.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	SITIS 2007: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL IMAGE TECHNOLOGIES & INTERNET BASED SYSTEMS
Uncontrolled Keywords:	Face recognition, Feature extraction
Subjects:	T Technology > T Technology (General) Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	29 Sep 2011 07:07
Last Modified:	21 Sep 2021 07:51
URII:	http://shdl.mmu.edu.my/id/eprint/2949

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