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Motion trajectory analysis is important for human motion recognition and human computer interaction. In this paper, we propose a flexible 3D trajectory indexing method for complex 3D motion recognition. Based on both point level and primitive-level descriptors, trajectories are represented in the sub-primitive level, the level between the point level and primitive level. Primitives are flexibly segmented...
Motion recognition based on trajectory is important for motion analysis. Complicated motion recognition is still a challenge in various applications of robot and automation. In this paper, we propose a novel framework with a new model, Scaled Indexing of General Shapes (S-IGS), for complicated motion recognition. The Scaled IGS is a quantified hierarchical model, representing 3D motion trajectories...
Motion trajectory description plays an important role in motion recognition for many robotic tasks. The previous methods are too high in computational cost for real time recognition. In this paper, we propose a novel indexing method for motion trajectories as a high level invariant descriptor. Trajectories are segmented into basic segments and represented in segment level rather than point level....
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