遮蔽を明示的にモデル化したLiDAR物体分類
Lidar-based Object Classification with Explicit Occlusion Modeling
LiDAR点群の物体検出・分類において、隣接物体間の遮蔽を点群の内在的性質として明示的にモデル化し、分類精度を向上させた研究。KITTIデータセットで有効性を検証した。
著者: Xiaoxiang Zhang, Hao Fu, Bin Dai
分類: cs.RO, cs.CV, eess.IV
原文アブストラクト
LIDAR is one of the most important sensors for Unmanned Ground Vehicles (UGV). Object detection and classification based on lidar point cloud is a key technology for UGV. In object detection and classification, the mutual occlusion between neighboring objects is an important factor affecting the accuracy. In this paper, we consider occlusion as an intrinsic property of the point cloud data. We propose a novel approach that explicitly model the occlusion. The occlusion property is then taken into account in the subsequent classification step. We perform experiments on the KITTI dataset. Experimental results indicate that by utilizing the occlusion property that we modeled, the classifier obtains much better performance.
