Classification of LiDAR Point Clouds Using Supervoxel-Based Detrended Feature and Perception-Weighted Graphical Model

Abstract

Interpretation of 3-D scene through LiDAR point clouds has been a hot research topic for decades. To utilize measured points in the scene, assigning unique tags to the points of the scene with labels linking to individual objects plays a crucial role in the analysis process. In this article, we present a supervised classification approach for the semantic labeling of laser scanning points. A novel method for extracting geometric features is proposed, removing redundant and insignificant information in the local neighborhood of the supervoxels. The proposed feature extraction method uses the supervoxel-based local neighborhood instead of points as basic elements, encapsulating the geometric features of local points. Based on the initial classification results, the graph-based optimization is used to spatially smooth the labeling results, based on the graphical model using the perception weighted edges. Benefiting from the graphbased optimization process, our supervised classification method required only a few training datasets. Experiments were carried out by comparing the semantic labeling results with manually generated ground truth datasets. The performance of the proposed methods with different characteristics was analyzed. By using our testing datasets, we have achieved an overall accuracy of better than 0.8 for assigning the measured points to eight semantic classes.

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“…Our proposed method for boundary refined supervoxel generation consist the detection of boundary points, and the refinement of boundary points. Firstly, based on the generated VCCS supervoxel, points within each supervoxel were defined by the distance from the point to the supervoxel center considering the local curvature exploring the spatial proximity of adjacent supervoxels in geodetic space [ 31 ]. If the distance was larger than a given threshold, which was empirically set to be one-half of the seed supervoxel resolution, the point was regarded as a boundary point.…”

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