The automatic recognition of facial expression presents a significant challenge to the pattern analysis and man-machine interaction research community. In this paper, a novel system is proposed to recognize human facial expressions based on the expression sketch. Firstly, facial expression sketch is extracted by an GPU-based real-time edge detection and sharpening algorithm from original gray image. Then, a statistical method, which is called Eigenexpress, is introduced to obtain the expression feature vectors for sketches. Finally, Modified Hausdorff distance(MHD) was used to perform the expression classification. In contrast to performing feature vector extraction from the gray image directly, the sketch based expression recognition reduces the feature vector's dimension first, which leads to a concise representation of the facial expression. Experiment shows our method is appreciable and convincible. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Wu, Q., Song, M., Bu, J., & Chen, C. (2006). Eigenexpress approach in recognition of facial expression using GPU. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3979 LNCS, pp. 12–20). Springer Verlag. https://doi.org/10.1007/11754336_2
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