基于视觉的人机共生手势识别

M. Bhuiyan, M. M. Islam, N. Begum, M. Hasanuzzaman, C. Liu, H. Ueno
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引用次数: 6

摘要

提出了一种基于视觉的人机共生手势识别系统。该系统以人脸的视觉信息为基础,通过对HSV颜色模型中图像肤色分割的连通分量分析和基于神经网络的模式匹配策略,从人脸手势识别入手。在手势识别方面,机器人通过发出指令来执行特定的任务。该系统能够识别由面部姿势组成的静态手势和面部运动的动态手势。经过一些实验,证明了该系统的有效性。该系统已与一个名为ldquoAIBOrdquo的娱乐机器人作为人机共生关系进行了演示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vision based gesture recognition for human-robot symbiosis
This paper presents a vision based gesture recognition system for human-robot symbiosis. The system is based on the visual information of the face and is commenced with the recognition of face gesture by connected component analysis of the skin color segmentation of images in HSV color model and neural network based pattern-matching strategies. On gesture recognition, robot is being instructed to perform certain tasks by issuing commands. The system is capable of recognizing static gestures comprised of the face poses, and dynamic gestures of face in motion. The effectiveness of the system has been justified over some experiments. The system has been demonstrated with an entertainment robot named ldquoAIBOrdquo as a human-robot symbiotic relationship.
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