Generic versus Salient Region-Based Partitioning for Local Appearance Face Recognition
نویسندگان
چکیده
In this paper, we investigate different partitioning schemes for local appearance-based face recognition. Five different salient regionbased 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.
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