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Why Recognition in a Statistics-based Face Recognition System Should be based on the Pure Face Portion: a Probabilistic Decision-based Proof

By Li-Fen Chen, Hong-Yuan Mark Liao, Ja-chen Lin and Chin-Chuan Han

Abstract

It is evident that the process of face recognition, by definition, should be based on the content of a face. The problem is: what is a "face"? Recently, a state-of-the-art statistics-based face recognition system, the PCA plus LDA approach, has been proposed [1]. However, the authors used "face" images that included hair, shoulders, face and background. Our intuition tells us that only a recognition process based on a "pure" face portion can be called face recognition. The mixture of irrelevant data may result in an incorrect set of decision boundaries. In this paper, we propose a statistics-based technique to quantitatively prove our assertion. For the purpose of evaluating how the different portions of a face image will influence the recognition results, a hypothesis testing model is proposed. We then implement the above mentioned face ..

Topics: statistics-based face recognition, face-only database, hypothesis testing
Year: 2000
OAI identifier: oai:CiteSeerX.psu:10.1.1.32.7922
Provided by: CiteSeerX
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