Advantages of exploiting projection structure for segmenting dense 3D point clouds
Bewley, Alex & Upcroft, Ben (2013) Advantages of exploiting projection structure for segmenting dense 3D point clouds. In Katupitiya, Jayantha, Guivant, Jose, & Eaton, Ray (Eds.) Proceedings of the 2013 Australasian Conference on Robotics and Automation, Australian Robotics & Automation Association, University of New South Wales, Sydney, NSW, pp. 1-8.
Timely and comprehensive scene segmentation is often a critical step for many high level mobile robotic tasks. This paper examines a projected area based neighbourhood lookup approach with the motivation towards faster unsupervised segmentation of dense 3D point clouds. The proposed algorithm exploits the projection geometry of a depth camera to find nearest neighbours which is time independent of the input data size. Points near depth discontinuations are also detected to reinforce object boundaries in the clustering process. The search method presented is evaluated using both indoor and outdoor dense depth images and demonstrates significant improvements in speed and precision compared to the commonly used Fast library for approximate nearest neighbour (FLANN) [Muja and Lowe, 2009].
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|Item Type:||Conference Paper|
|Keywords:||Scene segmentation, Mobile robotic tasks, Dense 3D point clouds, unsupervised segmentation, Depth camera|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2013 [please consult the authors]|
|Deposited On:||28 Jan 2014 01:26|
|Last Modified:||30 Jan 2014 04:22|
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