Evaluating the impact of point cloud downsampling on the robustness of Lidar-based object detection

Golarits, Marcell and Rózsa, Zoltán and Hamzaoui, Raouf and Allidina, Tanvir and Lu, Xin and Szirányi, Tamás (2024) Evaluating the impact of point cloud downsampling on the robustness of Lidar-based object detection. In: XI. Magyar Számítógépes Grafika és Geometria Konferencia. NJSZT, Budapest, pp. 126-133. ISBN 9789634219484

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Abstract

LiDAR-based 3D object detection relies on the relatively rich information captured by LiDAR point clouds. However, computational efficiency often requires the downsampling of these point clouds. This paper studies the impact of downsampling strategies on the robustness of a state-of-the-art object detector, namely PointPillars. We compare the performance of the approach under random sampling and farthest point sampling, evaluating the model’s accuracy in detecting objects across various downsampling ratios. The experiments were conducted on the popular KITTI dataset.

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