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Object Based Key Frame Selection for Hand Gesture Recognition

机译:基于对象的手势识别关键帧选择

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摘要

The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection., Hausdorff distance, Forward Algorithm and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed use to the hidden markov model and nonlinear time alignment model with key frame selection facility and gesture trajectory features for hand gesture recognition. Experimental results demonstrate the effectiveness of our proposed scheme for recognizing American Sign Language.
机译:手语识别是最流行的研究领域,涉及计算机视觉,模式识别和图像处理。它增强了静音人的沟通能力。在本文中,我们提出了一种基于对象的关键帧选择,将Hausdorff距离,正向算法和欧几里得距离用于手势识别的形状相似性。我们提出将其用于隐马尔可夫模型和具有关键帧选择工具和手势轨迹特征的非线性时间对齐模型用于手势识别。实验结果证明了我们提出的识别美国手语的方案的有效性。

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