Fusion of 3D-LIDAR and camera data for scene parsing |
| |
Institution: | 1. School of EEE, Nanyang Technological University, Singapore;2. DSO National Laboratories, Singapore;1. Laboratorio de Robótica, Institute of Engineering and Technology Universidad Autónoma de Cd. Juárez, Ave. del Charro 450 Norte, Juárez, Chih., 32310, MEXICO;2. CINVESTAV Campus Saltillo, Ramos Arizpe, Coahuila, MEXICO;3. Singapore University of Technology and Design, 20 Dover Drive, Singapore, 138682, SINGAPORE;1. Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai, China;2. LCFC, Arts et Métiers ParisTech, HESAM, Université de Lorraine, 4 rue Augustin Fresnel, 57078 Metz Cedex 3, France |
| |
Abstract: | Fusion of information gathered from multiple sources is essential to build a comprehensive situation picture for autonomous ground vehicles. In this paper, an approach which performs scene parsing and data fusion for a 3D-LIDAR scanner (Velodyne HDL-64E) and a video camera is described. First of all, a geometry segmentation algorithm is proposed for detection of obstacles and ground areas from data collected by the Velodyne scanner. Then, corresponding image collected by the video camera is classified patch by patch into more detailed categories. After that, parsing result of each frame is obtained by fusing result of Velodyne data and that of image using the fuzzy logic inference framework. Finally, parsing results of consecutive frames are smoothed by the Markov random field based temporal fusion method. The proposed approach has been evaluated with datasets collected by our autonomous ground vehicle testbed in both rural and urban areas. The fused results are more reliable than that acquired via analysis of only images or Velodyne data. |
| |
Keywords: | Scene parsing Velodyne scanner Camera Fuzzy logic Temporal fusion MRF Object detection RGBD |
本文献已被 ScienceDirect 等数据库收录! |
|