Convex Cut: A Realtime Pseudo-Structure Extraction Algorithm For 3d Point Cloud Data

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(2015)

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摘要
In this paper, a realtime pseudo-structure extraction algorithm for 3D indoor point cloud data (PCD) is proposed. This algorithm is called Convex Cut (CC) because of its two main steps: cutting the PCD with arbitrary planes, and extracting convex parts. CC can be used as a preprocessing module for other existing algorithms to extract static parts in dynamic environments or to represent a principal 3D model of a given PCD. Its calculation time is 24 milliseconds for 50k PCD on a consumer PC, and it yields a precision value of 0.90 and a recall value of 0.99 on average in highly dynamic and cluttered environments. Some possible applications are explained such as simultaneous localization and mapping in dynamic environments, efficient dense map representation, robust 3D scan matching with plane features, and natural motion planning.
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关键词
realtime pseudo-structure extraction algorithm,3D indoor point cloud data,convex cut,PCD,convex part extraction,CC,simultaneous localization and mapping,dense map representation,3D scan matching,natural motion planning
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