We present a novel approach that exploits shape context to recognize emotion from monocular dance image sequences. The method makes use of contour information as well as region-based shape information. The procedure of the method is as follows. First, we compute binary silhouette images and its bounding box from dance images. Next, we extract the quantitative features that represent the quality of the motion of a dance. Then, we find meaningful lowdimensional structures, removing redundant information but retaining essential information possessing high discrimination power, of the features using SVD (Singular Value Decomposition). Finally, we classify the low-dimensional features into predefined emotional categories using TDMLP (Time Delayed MultiLayer Perceptron). Experimental results demonstrate the validity of the proposed method. © Springer-Verlag 2004.
CITATION STYLE
Park, H., Park, J. I. I., Kim, U. M., & Woo, N. (2004). Emotion Recognition from Dance Image Sequences Using Contour Approximation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3138, 547–555. https://doi.org/10.1007/978-3-540-27868-9_59
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