基于对象的关键帧选择手势识别

2010 International Conference on Advances in Recent Technologies in Communication and Computing Pub Date : 2010-10-16 DOI:10.1109/ARTCOM.2010.80

Ketki P. Kshirsagar, D. Doye

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引用次数: 5

摘要

手语识别是计算机视觉、模式识别和图像处理等领域的研究热点。它提高了哑巴的沟通能力。本文提出了一种基于对象的关键帧选择方法。采用Hausdorff距离、前向算法和欧氏距离进行形状相似度识别。提出利用隐马尔可夫模型和非线性时间对齐模型结合关键帧选择功能和手势轨迹特征进行手势识别。实验结果证明了该方法对美国手语识别的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Object Based Key Frame Selection for Hand Gesture Recognition

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.

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来源期刊

2010 International Conference on Advances in Recent Technologies in Communication and Computing

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