An Adaptive Visual Gesture Based Interface for Human Machine Interaction in Intelligent Workspaces

A. Prieto, F. Bellas, R. Duro, F. López-Peña
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引用次数: 5

Abstract

This paper describes the implementation of an artificial neural network based adaptive hand positioning and gesture recognition system for multimodal interfaces in intelligent workspaces. The system is based on a stereo vision system and provides a series of mechanisms for an efficient segmentation of the arm-hand structure over the screen and its description in terms of moments that can be used by a neural network based structure in order to provide position and gesture classification results. These can be adapted to the user's desires through an interaction and feedback mechanism permitting a natural mutual learning process between the system and the human
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基于自适应视觉手势的智能工作空间人机交互界面
本文介绍了一种基于人工神经网络的智能工作空间多模态界面自适应手部定位与手势识别系统的实现。该系统基于立体视觉系统,提供了一系列有效分割屏幕上手臂-手结构的机制,并根据矩进行描述,这些矩可用于基于神经网络的结构,以提供位置和手势分类结果。这些可以通过交互和反馈机制来适应用户的需求,允许系统和人之间自然的相互学习过程
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