面向远程人机交互的手势识别鲁棒实现

2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2015-10-01 DOI:10.1109/ICITEED.2015.7408950

Jakkrit Dulayatrakul, Pawin Prasertsakul, T. Kondo, I. Nilkhamhang

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引用次数: 14

摘要

提出了一种鲁棒的远程人机交互手势识别算法，并对该算法进行了优化，使其能够在嵌入式平台上实现。采用色调饱和值(HSV)阈值和单位梯度矢量(UGV)背景相减方法来克服与光照条件变化相关的常见问题。顶帽转换用于检测手指和手势，这些手指和手势被转换为远程控制媒体播放器的命令输入。实验结果表明，该算法在嵌入式板上运行高效、准确，每个手势的平均计算时间为143毫秒，对光照变化具有较强的鲁棒性。

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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Robust implementation of hand gesture recognition for remote human-machine interaction

A robust hand gesture recognition algorithm for remote human-machine interaction is proposed that has been optimized for implementation on an embedded platform. Hue-saturation-value (HSV) thresholding and unit-gradient vector (UGV) background subtraction methods are employed to overcome common issues related to variations in lighting conditions. Top-hat transformation is used to detect fingers and hand gestures, which are translated to command inputs for remotely controlling a media player. Experimental results demonstrate that the algorithm performs efficiently and accurately on an embedded board with an average computational cost of 143 millisecond per gesture and is robust to changes in illumination.

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2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE)

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