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Planar patch extraction with noisy depth data

机译:使用嘈杂的深度数据进行平面补丁提取

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This paper presents an algorithm for extracting planar patches by integrating both intensity and range data provided by a stereo system. For dealing with noisy and sparse range data, the initial segmentation is based on intensity information, and then the resulted regions are thresholded using depth data. This new algorithm, different from the existing ones that use only range data in the segmentation process, produces accurate planar patches that are then used for building a panoramic image-based model for mobile robot navigation.
机译:本文介绍了一种通过集成立体声系统提供的强度和范围数据来提取平面贴片的算法。为了处理嘈杂和稀疏范围数据,初始分割基于强度信息,然后使用深度数据阈值阈值。这种新的算法,与仅在分段过程中仅使用范围数据的现有算法,产生精确的平面贴片,然后用于构建基于全景的移动机器人导航模型。

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