Action Recognition Online with Hierarchical Self-Organizing Maps

Zahra Gharaee, P. Gärdenfors, Magnus Johnsson
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引用次数: 11

Abstract

We present a hierarchical self-organizing map based system for online recognition of human actions. We have made a first evaluation of our system by training it on two different sets of recorded human actions, one set containing manner actions and one set containing result actions, and then tested it by letting a human performer carry out the actions online in real time in front of the system's 3D-camera. The system successfully recognized more than 94% of the manner actions and most of the result actions carried out by the human performer.
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基于层次自组织地图的在线动作识别
提出了一种基于层次自组织地图的人类行为在线识别系统。我们对我们的系统进行了第一次评估,方法是在两组不同的人类行为记录上进行训练,一组包含方式行为,另一组包含结果行为,然后通过让人类表演者在系统的3d相机前实时在线执行这些行为来测试它。该系统成功识别了超过94%的方式动作和大多数由人类表演者执行的结果动作。
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