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Silhouette-based multi-view human action recognition in video

机译:视频中基于轮廓的多视角人的动作识别

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In this paper, a human action recognition method is presented where pose features are represented using contour points of the human silhouette, and actions are learned by using sequences of multi-view contour points. The differences and divergences among actors performing the same action are handled by considering variations in shape and speed. Experimental results on the IXMAS dataset show promising success rates, exceeding that of existing multi-view human action recognition state-of-the-art techniques.
机译:在本文中,提出了一种人类动作识别方法,其中使用人体轮廓的轮廓点表示姿势特征,并使用多视图轮廓点的序列学习动作。通过考虑形状和速度的变化来处理执行相同动作的演员之间的差异和分歧。 IXMAS数据集上的实验结果显示出成功的成功率,超过了现有的多视图人类动作识别最新技术。

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