Depth Image-based Object Segmentation Scheme for Improving Human Action Recognition

초록

Human action recognition using the 3D camera for surveillance applications is a promising alternative approach to the conventional 2D camera based surveillance. We propose a depth image-based object segmentation scheme for improving human action recognition. Experimental results show that the average accuracy of the dangerous event detection is improved by about 15% when using the proposed object segmentation scheme.

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