Approaches for global-based action representations for games and action understanding

In this paper, we present some spatio-temporal (XYT) approaches for global-based action representation at the top of the motion history image method. Action representations can be considered as image templates, which can be useful for understanding various actions or gestures as well as for recognition and analysis. These spatio-temporal representations can be useful for various games environments. The motion history image represents how motion moves in image sequence. We present our SURF-based history image. In this method, we extract visual features to select candidate points based on the SURF detector. Then we extract motion features to calculate motion vectors at each point by employing optical flow. In this paper, we also propose a method called intensity-accumulated image method that can manage partial occlusion or some missing moving information. Based on our analyses, we strongly feel that our proposed methods - SURF-based motion history image method and the intensity-accumulated image method can be useful for various applications related to games, gesture and action understanding for analyses.