Recognition of hand gesture using hidden Markov model

Khan Mohammad Irteza, Sheikh Mohammad Masudul Ahsan, Razib Chandra Deb
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引用次数: 3

Abstract

In this paper we proposed a recognition system for hand gesture in 3D environment by using only a single camera. For calculating the relative motion towards the camera, generally a depth sensing device is needed. In order to remove that, we proposed an approach of using the change of the area of the hand in input image. Using skin color; we detect the hand from the input image sequences and then we process the data for feature extraction. Three features are proposed for effectively recognize the gesture by our system. These are orientation, area and angle of the palm. As we proposed our system for dynamic gesture, Hidden Markov Model is utilized to recognize the gesture. In our lab environment our proposed system shows very promising result and we were able to achieve about 80.67% recognition rate on average. The system that we proposed will not only help to recognize the gesture of hand accurately but also lessen the cost for implementing this kind of system because of using minimal number of hardware.
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基于隐马尔可夫模型的手势识别
本文提出了一种基于单摄像头的三维环境下的手势识别系统。为了计算相对于相机的运动,通常需要一个深度感测装置。为了消除这一问题,我们提出了一种利用输入图像中手部面积变化的方法。使用肤色;我们从输入的图像序列中检测手,然后对数据进行特征提取。为使系统有效识别手势,提出了三个特征。这些是手掌的方向,面积和角度。在我们提出的动态手势系统中,使用隐马尔可夫模型来识别手势。在我们的实验室环境中,我们所提出的系统显示出非常好的结果,我们能够达到平均80.67%的识别率。我们提出的系统不仅有助于准确识别手势,而且由于使用了最少的硬件,降低了实现这种系统的成本。
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