Fast planar segmentation of depth images

Hani Javan Hemmat; Arash Pourtaherian; Egor Bondarev; Peter H. N. de With

doi:10.1117/12.2083340

16 March 2015 Fast planar segmentation of depth images

Hani Javan Hemmat, Arash Pourtaherian, Egor Bondarev, Peter H. N. de With

Proceedings Volume 9399, Image Processing: Algorithms and Systems XIII; 93990I (2015) https://doi.org/10.1117/12.2083340
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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.

Citation Download Citation

Hani Javan Hemmat, Arash Pourtaherian, Egor Bondarev, and Peter H. N. de With "Fast planar segmentation of depth images", Proc. SPIE 9399, Image Processing: Algorithms and Systems XIII, 93990I (16 March 2015); https://doi.org/10.1117/12.2083340

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