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Proceedings Paper

Real-time multi-criteria classification of facial images
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Paper Abstract

We proposes a practical technique for the classification of facial images across multiple criteria, such as: gender, age, ethnicity, expression, and others. The technique uses a novel form of Gabor-based features followed by the application of the PCA and LDA algorithms. The computation of class scores in the context of nearest centroid classification is also novel, and relies, in part, on properties of the proposed features. We demonstrate that the proposed form of Gabor features is particularly suitable for achieving simultaneous classification. The reported results are obtained using a set of standard databases and include comparisons against known state-of-the-art algorithms. The utility of the proposed scheme is demonstrated by practical applications requiring multiple classification results to be obtained in real time while using typical consumer devices (cellphones, tablets, PCs) as computing platforms.

Paper Details

Date Published: 6 September 2019
PDF: 12 pages
Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111371T (6 September 2019); doi: 10.1117/12.2532068
Show Author Affiliations
Radoslav Marinov, Brightcove, Inc. (United States)
Zhifeng Chen, Univ. of Florida (United States)
Yuriy Reznik, Brightcove, Inc. (United States)

Published in SPIE Proceedings Vol. 11137:
Applications of Digital Image Processing XLII
Andrew G. Tescher; Touradj Ebrahimi, Editor(s)

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