Face recognition from color images using sparse projection analysis

Authors:
Vitomir Štruc;Nikola Pavešić
Affiliations:
Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia;Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
Venue:
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Year:
2010

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Abstract

The paper presents a novel feature extraction technique for face recognition which uses sparse projection axes to compute a low- dimensional representation of face images. The proposed technique derives the sparse axes by first recasting the problem of face recognition as a regression problem and then solving the new (under-determined) regression problem by computing the solution with minimum L1 norm. The developed technique, named Sparse Projection Analysis (SPA), is applied to color as well as grey-scale images from the XM2VTS database and compared to popular subspace projection techniques (with sparse and dense projection axes) from the literature. The results of the experimental assessment show that the proposed technique ensures promising results on un-occluded as well occluded images from the XM2VTS database.