机器人遥控增强现实环境中的物体感知研究

Chensheng Wang, Fei Wang, T. Wiegers
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引用次数: 0

摘要

物体识别是计算机视觉领域的研究热点之一。现有的目标识别技术是基于图像处理的,往往无法恢复目标的拓扑信息。本文在分析人类感知习惯的基础上,提出了一种新的目标识别策略。该方法利用现有的形状知识耦合来感知场景中的物体。并设计了一种机制,通过在遇到新对象时将形状知识存入存储库来增长系统智能。这使得系统不断地变得越来越智能。此外,该策略有利于在存储库的支持下重建整个对象信息。在机器人遥控增强现实环境中进行的实验结果表明,所提出的策略对设计的应用是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Object Perception in Enhanced Reality Environment for Robot Telecontrol
Object recognition is one of the hot topics in computer vision. Existing techniques for object recognition are based on image processing, which tends to be incapable to recover the topological information of the object. In this paper, based on the analysis of human perceptual habit, a novel strategy for object recognition is proposed. The method perceives an object in the scene by means of existing shape knowledge coupling. And a mechanism is designed to grow the system intelligence by depositing the shape knowledge into a repository once a new object is encountered. This makes the system be in a constant way to become more and more intelligent. In addition, the proposed strategy is advantageous in rebuilding the whole object information with the support of the repository. Experiment results carried out in the enhanced reality environment for robot telecontrol shows that the proposed strategy is both valid and effective for the designed application.
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