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A panoramic vision system for human-robot interaction

机译:用于人机交互的全景视觉系统

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We have proposed a new approach for solving a fundamental issue in HRI, that is, how to properly detect and identify people in everyday environments since some conditions might make it a difficult task. For that, fisheye cameras are used since they provide panoramic vision and one or two of them allow to cover the whole workspace. A modified background maintenance approach was developed for fast, robust motion detection; while person identification for interaction is dealt with Viola-Jones classifier, although, instead of searching in the whole image, its input is only composed of the detected moving elements. Moreover, in order to avoid restricting the system autonomy by requiring the person has to face the system any time, once a person is identified as a target for interaction, they are tracked by using another designed method. We have also carried out an implementation of the proposed approach and a comparative experiment to assess its feasibility.
机译:我们提出了一种新的方法来解决HRI中的一个基本问题,即如何在日常环境中正确地检测和识别人员,因为某些条件可能使之困难重重。为此,使用了鱼眼镜头摄像机,因为它们可以提供全景视野,并且其中一到两个可以覆盖整个工作区。开发了一种改进的背景维护方法,可进行快速,强大的运动检测;尽管使用Viola-Jones分类器来处理用于交互的人员识别,但是并不是在整个图像中进行搜索,其输入仅由检测到的移动元素组成。而且,为了避免由于要求人员必须随时面对系统而限制系统自治性,一旦将人员标识为交互目标,就可以使用另一种设计的方法对其进行跟踪。我们还对建议的方法进行了实施,并进行了比较实验以评估其可行性。

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