Gesture analysis for human-robot interaction

Kyekyung Kim, Keun-Chang Kwak, Subrahmanyam. Ch
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引用次数: 43

Abstract

This paper is to present gesture analysis for human-robot interaction. Gesture analysis is consisted of four processes such as detecting of hand in bimanual movements, splitting of a meaning gesture region from image stream, extracting features and recognizing gesture. Skin color analysis, image motion detection and shape information are used to detect bimanual hand movements and gesture spotting. Skin color information for tracking hand gesture is obtained from face detection region. The velocity of moving hand is calculated for detecting a meaning gesture region from consecutive image frames. Combined gesture features such as structural and statistical features are extracted from image stream. We have experimented to evaluate detection of bimanual hand movements and gesture recognition with a camera, which is pan/tilt and a single camera that is mounted on mobile robot. Performance evaluation of gesture recognition has experimented using ETRI database and an encouraging recognition rate of 89 % has been obtained
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人机交互的手势分析
本文主要研究人机交互中的手势分析。手势分析包括手部动作的检测、图像流中意义手势区域的分割、特征提取和手势识别四个过程。肤色分析、图像运动检测和形状信息用于检测双手动作和手势识别。从人脸检测区域获取用于跟踪手势的肤色信息。计算移动的手的速度以从连续的图像帧中检测有意义的手势区域。从图像流中提取结构特征和统计特征等组合手势特征。我们已经进行了实验,评估用一个摄像头检测双手动作和手势识别,这个摄像头是平移/倾斜的,一个安装在移动机器人上的单摄像头。利用ETRI数据库对手势识别进行了性能评价实验,获得了89%的识别率
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