23 June 2003 Face recognition with non-negative matrix factorization
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Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003); doi: 10.1117/12.502365
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland
Abstract
A face can conceptually be represented as a collection of sparsely distributed parts: eyes, nose, mouth etc.We use Non-negative Matrix Factorization (NMF) to yield sparse representation of localized features to represent distributed parts over a human face. This paper explores the potential of NMF for face recognition and the possibilities for gender-based features in face reconstruction. Further, we compare the results of NMF with other common face recognition methods.
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Menaka Rajapakse, Lonce Wyse, "Face recognition with non-negative matrix factorization", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); doi: 10.1117/12.502365; https://doi.org/10.1117/12.502365
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KEYWORDS
Computer programming

Databases

Facial recognition systems

Principal component analysis

Eye

Signal to noise ratio

Wavelets

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