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Recent methods and databases in vision-based hand gesture recognition: A review

机译:基于视觉的手势识别的最新方法和数据库:综述

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Successful efforts in hand gesture recognition research within the last two decades paved the path for natural human-computer interaction systems. Unresolved challenges such as reliable identification of gesturing phase, sensitivity to size, shape, and speed variations, and issues due to occlusion keep hand gesture recognition research still very active. We provide a review of vision-based hand gesture recognition algorithms reported in the last 16 years. The methods using RGB and RGB-D cameras are reviewed with quantitative and qualitative comparisons of algorithms. Quantitative comparison of algorithms is done using a set of 13 measures chosen from different attributes of the algorithm and the experimental methodology adopted in algorithm evaluation. We point out the need for considering these measures together with the recognition accuracy of the algorithm to predict its success in real-world applications. The paper also reviews 26 publicly ; available hand gesture databases and provides the web-links for their download.
机译:在过去的二十年中,手势识别研究取得了成功,为自然的人机交互系统铺平了道路。未解决的挑战(例如可靠识别手势阶段,对尺寸,形状和速度变化的敏感性)以及由于闭塞引起的问题使手势识别研究仍然非常活跃。我们对过去16年中报告的基于视觉的手势识别算法进行了回顾。回顾了使用RGB和RGB-D相机的方法,并对算法进行了定量和定性比较。使用从算法的不同属性和算法评估中采用的实验方法中选择的13种量度对算法进行定量比较。我们指出有必要考虑这些措施以及算法的识别精度,以预测其在实际应用中的成功。该文件还公开评论了26个;可用的手势数据库,并提供下载链接。

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