Face Recognition Using a Face-Only Database : a New Approach
Hong-Yuan Mark Liao, Chin‐Chuan Han, Gwo‐Jong Yu, Hsiao-Rong Tyan, Meng Chang Chen, Liang-Hua Chen · 1997
In this paper, a coarse-to-fine, LDA-based face recognition system is proposed. Through careful implementation, we found that the databases adopted by two state-of-the-art face recognition systems[1,2] were incorrect because they mistakenly use some non-face portions for face recognition. Hence, a face-only database is used in the proposed system. Since the facial organs on a human face only differ slightly from person to person, the decision-boundary determination process is tougher in this system than it is in conventional approaches. Therefore, in order to avoid the above mentioned ambiguity problem, we propose to retrieve a closest subset of database samples instead of retrieving a single sample. The proposed face recognition system has several advantages. First, the system is able to deal with a very large database and can thus provide a basis for efficient search. Second, due to its design nature, the system can handle the defocus and noise problems.Third, the system is faster than the autocorrelation plus LDA approach [1] and the PCA plus LDA approach [2], which are believed to be two statistics-based, state-of-the-art face recognition systems. Experimental results prove that the proposed method is better than traditional methods in terms of efficiency and accuracy.