人机交互中手势的分布与识别

N. Otero, S. Knoop, Chrystopher L. Nehaniv, D. Syrdal, K. Dautenhahn, R. Dillmann
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引用次数: 21

摘要

本文提出了一种针对教学场景中手势的人类活动识别方法,以及在无约束人机交互(HRI)中对人类手势的用户研究的设置和结果。用户研究分析了几个方面:手势的分布,这些手势的关系和特征,以及不同手势类型在人机教学场景中的可接受性。然后根据活动识别方法对结果进行评估。主要的努力是弥合人类活动识别方法与自然发生或至少可接受的HRI手势之间的差距。我们的目标是双重的:为识别方法提供HRI中人类活动的特征和特征的信息和需求,以及识别人类对人机教学场景中手势识别的偏好和需求
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distribution and Recognition of Gestures in Human-Robot Interaction
This paper presents an approach for human activity recognition focusing on gestures in a teaching scenario, together with the setup and results of user studies on human gestures exhibited in unconstrained human-robot interaction (HRI). The user studies analyze several aspects: the distribution of gestures, relations, and characteristics of these gestures, and the acceptability of different gesture types in a human-robot teaching scenario. The results are then evaluated with regard to the activity recognition approach. The main effort is to bridge the gap between human activity recognition methods on the one hand and naturally occuring or at least acceptable gestures for HRI on the other. The goal is two-fold: to provide recognition methods with information and requirements on the characteristics and features of human activities in HRI, and to identify human preferences and requirements for the recognition of gestures in human-robot teaching scenarios
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