Shape-Based Features for Optimized Hand Gesture Recognition

R. Priyanka, Prahanya Sriram, N. JayasreeL., Angelin Gladston
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引用次数: 2

Abstract

Gesture recognition is the most intuitive form of human-computer interface. Hand gestures provide a natural way for humans to interact with computers to perform a variety of different applications. However, factors such as complexity of hand gesture structures, differences in hand size, hand posture, and environmental illumination can influence the performance of hand gesture recognition algorithms. Considering the above factors, this paper aims to present a real time system for hand gesture recognition on the basis of detection of some meaningful shape-based features like orientation, center of mass, status of fingers, thumb in terms of raised or folded fingers of hand and their respective location in image. The internet is growing at a very fast pace. The use of web browser is also growing. Everyone has at least two or three most frequently visited website. Thus, in this paper, effectiveness of the gesture recognition and its ability to control the browser via the recognized hand gestures are experimented and the results are analyzed.
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优化手势识别的基于形状的特征
手势识别是最直观的人机界面形式。手势为人类与计算机交互以执行各种不同的应用程序提供了一种自然的方式。然而,手势结构的复杂性、手的大小差异、手势姿势和环境光照等因素都会影响手势识别算法的性能。考虑到以上因素,本文旨在通过检测一些有意义的形状特征,如方向、质心、手指的状态、拇指在举手或折叠手指中的位置以及它们在图像中的位置,提出一种实时的手势识别系统。互联网正在以非常快的速度发展。网络浏览器的使用也在增长。每个人都至少有两三个最常访问的网站。因此,本文对手势识别的有效性和通过识别的手势控制浏览器的能力进行了实验,并对实验结果进行了分析。
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