基于cfnn手势模型的人机交流

A. Várkonyi-Kóczy, B. Tusor
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引用次数: 1

摘要

最近,智能环境的使用已经变得流行,以使日常生活更舒适,提高人类的生活质量。本文介绍了一种手部姿态和手势建模与识别系统,该系统可以作为一个接口,通过简单的手势与智能空间进行通信。该系统利用模糊神经网络将检测手的预处理数据转化为特征模型,并在此模型的基础上进行模糊推理,确定实际手的姿态。最后,从检测到的手势序列中,系统可以识别出用户的手势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Man-machine communication via CFNN-based hand sign models
Recently, the usage of smart environments has become popular, in order to make everyday living more comfortable and to improve the quality of live of humans. In this paper, a hand posture and gesture modeling and recognition system is introduced, which can be used as an interface to make possible communication with the Intelligent Space by simple hand gestures. The system transforms preprocessed data of the detected hand into a feature model by using fuzzy neural networks and based on this model determines the actual hand posture applying fuzzy inference. Finally, from the sequence of detected hand postures, the system can recognize the hand gesture of the user.
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