A new face database and evaluation of face recognition techniques

This paper introduces ELA5, a new image database that is suitable for experimentation within the face recognition domain. Its design attempts to cover a variety of scenarios encompassing pose and illumination variations, different facial expressions and occlusion. In addition, established computational techniques such as Principal Component Analysis (PCA) and Multilinear PCA, combined with Fisher/Linear Discriminant Analysis (LDA) are evaluated and comparative results display their strengths and weaknesses in settings that simulate real-world conditions.

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