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Proceedings Paper

Fast planar segmentation of depth images
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Paper Abstract

One of the major challenges for applications dealing with the 3D concept is the real-time execution of the algorithms. Besides this, for the indoor environments, perceiving the geometry of surrounding structures plays a prominent role in terms of application performance. Since indoor structures mainly consist of planar surfaces, fast and accurate detection of such features has a crucial impact on quality and functionality of the 3D applications, e.g. decreasing model size (decimation), enhancing localization, mapping, and semantic reconstruction. The available planar-segmentation algorithms are mostly developed using surface normals and/or curvatures. Therefore, they are computationally expensive and challenging for real-time performance. In this paper, we introduce a fast planar-segmentation method for depth images avoiding surface normal calculations. Firstly, the proposed method searches for 3D edges in a depth image and finds the lines between identified edges. Secondly, it merges all the points on each pair of intersecting lines into a plane. Finally, various enhancements (e.g. filtering) are applied to improve the segmentation quality. The proposed algorithm is capable of handling VGA-resolution depth images at a 6 FPS frame-rate with a single-thread implementation. Furthermore, due to the multi-threaded design of the algorithm, we achieve a factor of 10 speedup by deploying a GPU implementation.

Paper Details

Date Published: 16 March 2015
PDF: 8 pages
Proc. SPIE 9399, Image Processing: Algorithms and Systems XIII, 93990I (16 March 2015); doi: 10.1117/12.2083340
Show Author Affiliations
Hani Javan Hemmat, Technische Univ. Eindhoven (Netherlands)
Arash Pourtaherian, Technische Univ. Eindhoven (Netherlands)
Egor Bondarev, Technische Univ. Eindhoven (Netherlands)
Peter H. N. de With, Technische Univ. Eindhoven (Netherlands)


Published in SPIE Proceedings Vol. 9399:
Image Processing: Algorithms and Systems XIII
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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