使用多个阴影图像占用空间

M. Langer, G. Dudek, S. Zucker
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引用次数: 28

摘要

解决了在移动机器人环境中使用视频图像估计3D空间占用的问题。一个静止的机器人从单一视点观察一个混乱的场景,第二个机器人从一系列方向照亮场景,从而产生一系列灰度图像。利用连续图像的差值计算阴影图像序列。问题是如何从这些影子图像中计算空闲空间和已占用空间。这个问题的解决方案以地形场景的特殊情况而闻名。作者通过两个关键的观察结果将这些解决方案推广到非地形场景。首先,在非地形场景的阴影图像上有一个子集约束,它允许通过基于地形的技术恢复非地形场景的可见表面。其次,阴影图像的剩余区域提供了这些可见表面隐藏的占用空间的保守估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Space occupancy using multiple shadowimages
Addresses the problem of estimating 3D space occupancy using video imagery in the context of mobile robotics. A stationary robot observes a cluttered scene from a single viewpoint, and a second robot illuminates the scene from a sequence of directions thus producing a sequence of grey-level images. Differences of successive images are used to compute a sequence of shadowimages. The problem is to compute free space and occupied space from these shadowimages. Solutions to this problem are known for the special case of terrain scenes. The authors generalize these solutions to non-terrain scenes by making two key observations. First, there is a subset constraint on the shadowimages of a non-terrain scene, which allows the visible surfaces of a non-terrain scene to be recovered by a terrain-based technique. Second, the remaining regions of the shadowimages provide a conservative estimate of the occupied space hidden by these visible surfaces.
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