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In this paper, we conduct a comprehensive study to identify the most discriminative features that address the interpersonal variability to perform efficient human emotion recognition task. We consider three commonly used feature extraction techniques, namely, the Local Binary Patterns (LBP), the Scale-Invariant Feature Transform (SIFT) and the curvelet transforms to extract features from the images...
In this paper, we present a machine learning approach for subject independent human action recognition using depth camera, emphasizing the importance of depth in recognition of actions. The proposed approach uses the flow information of all 3 dimensions to classify an action. In our approach, we have obtained the 2-D optical flow and used it along with the depth image to obtain the depth flow (Z motion...
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