Fast 3D object segmentation using DBSCAN clustering based on supervoxel

Tuo Yao; Qinghua Yang; Rui Zhang

doi:10.1117/12.2643697

9 October 2022 Fast 3D object segmentation using DBSCAN clustering based on supervoxel

Tuo Yao, Qinghua Yang, Rui Zhang

Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122461E (2022) https://doi.org/10.1117/12.2643697
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China

Abstract

For visual perception of indoor mobile robots, real-time segmentation of 3D objects is a very challenging problem. Due to the complexity and disorder of indoor point cloud data, many methods have been proposed to improve the segmentation accuracy, which most of them cannot meet the requirement of rapidity. Therefore, this paper proposes a method for fast segmentation of 3D point clouds based on supervoxel density clustering. First, the ground under the indoor scene is removed by using plane fitting algorithm and the point cloud data after ground removal is denoised at the same time. Then, the target object is over-segmented to obtain the supervoxels with local geometric features. The core points of the nearest neighbors at the center of the supervoxels are searched out using the kdtree indexing acceleration. Finally, the density clustering of the supervoxels is performed based on the core point density up to. Experimental results on publicly available datasets show that our proposed method can effectively improve the speed of the algorithm while ensuring accuracy.

Citation Download Citation

Tuo Yao, Qinghua Yang, and Rui Zhang "Fast 3D object segmentation using DBSCAN clustering based on supervoxel", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122461E (9 October 2022); https://doi.org/10.1117/12.2643697

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KEYWORDS

Clouds

Image segmentation

Detection and tracking algorithms

3D acquisition

3D vision

Data modeling

Data processing

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