不依赖视点的手势识别系统

Shen Wu, F. Jiang, Debin Zhao, Shaohui Liu, Wen Gao
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引用次数: 2

摘要

本文创造性地提出了一种基于Kinect传感器的无视点手势识别系统。通过深度图像构建用户点云。然后,我们估计当前最优视点,即前方,并将点云投影到该方向。通过这一过程,我们在很大程度上克服了观点依赖问题。为了匹配手部类型,我们提出了一个改进的形状上下文来描述每个手势,并使用匈牙利算法来计算匹配度。我们的方法非常简单,但实验结果证明,通过这种方法可以独立于视点识别手势,并且精度很高。此外,该算法速度快,鲁棒性好,可以实时应用于各种现实场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Viewpoint-independent hand gesture recognition system
In this paper, we creatively present a viewpoint-free hand gesture recognition system based on Kinect sensor. Through depth image, we build Point Clouds of user. Then, we estimate the current optimal viewpoint, i.e., the front, and project Point Clouds to that direction. Through that process we in great extent overcome the viewpoint-dependency issue. To match hand types, we propose an improved shape context to describe each hand gesture and use the Hungarian algorithm to calculate match degree. Our method is quite straightforward, however the experimental results prove that by this means gestures can be recognized independent of viewpoints with great accuracy. Besides, it is fast and robust, thus can be applied under various realistic scenarios in realtime.
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