Although color texture features have proven to be highly effective for face analysis, the comparisons between the color texture features have not been presented in the literature. The aim of this paper is to find the best way for combining color and texture features for face analysis. For this purpose, four different approaches (proposed for face recognition or facial expression recognition) of extracting color texture features are reviewed and compared through extensive experiments. Experimental results show that the texture feature extracted using color vector can achieve the highest recognition performances for both face recognition and facial expression recognition, among the color texture features presented in this paper. © 2013 Springer-Verlag.
CITATION STYLE
Lee, S. H., Kim, H., & Ro, Y. M. (2013). A comparative study of color texture features for face analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7786 LNCS, pp. 265–280). https://doi.org/10.1007/978-3-642-36700-7_21
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