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In this paper, we propose a 3D template-based human action detection base on volume pattern matching. A volume pattern is obtained by detecting the principal plane from a space-time patch using the 3D moment-preserving technique. Instead of segmentation and detailed shape representation, the objective of this research is to develop and apply computer vision methods that explore the structure of a space-time template by volume pattern matching to detect the human action from a larger video sequence. A voting scheme based on volume-based Generalized Hough transform (VBGHT) is presented to provide the 3D template matching and search method, which is robust to orientation, position, and motion. Experimental results show that the proposed method gives good performance in terms of detection accuracy and robustness.