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Graph-based segmentation for colored 3D laser point clouds

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3 Author(s)
Strom, J. ; Dept. of Comput. Sci. & Eng., Univ. of Michigan, Ann Arbor, MI, USA ; Richardson, Andrew ; Olson, E.

We present an efficient graph-theoretic algorithm for segmenting a colored laser point cloud derived from a laser scanner and camera. Segmentation of raw sensor data is a crucial first step for many high level tasks such as object recognition, obstacle avoidance and terrain classification. Our method enables combination of color information from a wide field of view camera with a 3D LIDAR point cloud from an actuated planar laser scanner. We extend previous work on robust camera-only graph-based segmentation to the case where spatial features, such as surface normals, are available. Our combined method produces segmentation results superior to those derived from either cameras or laser-scanners alone. We verify our approach on both indoor and outdoor scenes.

Published in:

Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on

Date of Conference:

18-22 Oct. 2010