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Generic versus salient region-based partitioning for local appearance face recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2009) 5558 LNCS 367-375
DOI: 10.1007/978-3-642-01793-3_38
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Abstract

In this paper, we investigate different partitioning schemes for local appearance-based face recognition. Five different salient region- based partitioning approaches are analyzed and they are compared to a generic partitioning scheme. Extensive experiments have been conducted on the AR, CMU PIE, FRGC, Yale B, and Extend Yale B face databases. The experimental results show that generic partitioning provides better performance than salient region-based partitioning schemes. © Springer-Verlag Berlin Heidelberg 2009.

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Ekenel, H. K., & Stiefelhagen, R. (2009). Generic versus salient region-based partitioning for local appearance face recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5558 LNCS, pp. 367–375). https://doi.org/10.1007/978-3-642-01793-3_38

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