Improved voxel-based point cloud feature extraction algorithm

Abstract

In previous voxel-based object detection models, the Point Cloud Feature Extraction module (VFE) overlooked the uneven distribution of points within voxels, and as a result, it did not address the issues caused by non-uniform sampling of point clouds. Recognizing this limitation, this paper introduces a new module, VFEPlus, to enhance the feature extraction process. VFEPlus utilizes kernel density estimation and nonlinear transformations to extract the inverse density factors from the point cloud data. This allows for the extraction of point cloud features with density information, thus improving the detection performance that was previously compromised by the non-uniform distribution of point clouds. Experimental comparisons on publicly available datasets demonstrate that this module achieves higher accuracy.