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- W55902164 abstract "In this paper we first present an effective image description method for facial expression recognition, which is a variation of local directional pattern (LDP). Then we introduce weightings on the modular’s LDP and investigate the effect on recognition rates with different weightings. Finally, the overlapped block is proposed when using LDP and proposed method. For recognition, this paper adopts PCA+LDP subspace method for feature reduction, and the nearest neighbor classifier is used in classification. The results of extensive experiments on benchmark datasets JAFFE and Cohn-Kanade illustrate that the proposed method not only can obtain better recognition rate but also have speed advantage. Moreover, the appropriately selected weightings and regional overlapping can improve recognition rates for both proposed method and LDP method." @default.
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- W55902164 date "2011-01-01" @default.
- W55902164 modified "2023-09-26" @default.
- W55902164 title "A Variation of Local Directional Pattern and Its Application for Facial Expression Recognition" @default.
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- W55902164 doi "https://doi.org/10.1007/978-3-642-27183-0_5" @default.
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