Face recognition with non-negative matrix factorization

Menaka Rajapakse; Lonce Wyse

doi:10.1117/12.502365

23 June 2003 Face recognition with non-negative matrix factorization

Menaka Rajapakse, Lonce Wyse

Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/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.

Citation Download Citation

Menaka Rajapakse and Lonce Wyse "Face recognition with non-negative matrix factorization", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); https://doi.org/10.1117/12.502365

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