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首页> 外文会议>International Conference on Image and Signal Processing >Improving of Gesture Recognition Using Multi-hypotheses Object Association
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Improving of Gesture Recognition Using Multi-hypotheses Object Association

机译：使用多假设对象关联提高手势识别

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摘要

Gesture recognition plays an important role in Human Computer Interaction (HCI) but in most HCI systems, the user is limited to use only one hand or two hands under optimal conditions. Challenges are for instance non-homogeneous backgrounds, hand-hand or hand-face overlapping and brightness modifications. In this research, we have proposed a novel approach that solves the ambiguities occurred due to the hand overlapping robustly based on multi-hypotheses object association. This multi-hypotheses object association builds the basis for the tracking in which the hand trajectories are computed and this leads us to extract the features. The gesture recognition phase takes the extracted features and classifies them through Hidden Markov Model (HMM).
机译：手势识别在人机交互（HCI）中起着重要作用，但在大多数HCI系统中，用户仅限于在最佳条件下仅使用一只手或两只手。挑战例如是非均匀的背景，手工或手脸重叠和亮度修改。在这项研究中，我们提出了一种新的方法，解决了由于基于多假设对象关联的手重叠而发生的歧义。该多假设对象关联构建了计算手动轨迹的跟踪的基础，这导致我们提取该功能。手势识别阶段采用提取的特征并通过隐藏的马尔可夫模型（HMM）对它们进行分类。

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