Vehicle pose estimation from drive recorder images by monocular SLAM and matching with rendered 3D point cloud of surrounding environment

Akiyoshi Kurobe, Hisashi Kinoshita, Hideo Saito

研究成果: Conference article

抜粋

Vehicle pose estimation is a vital technology for reconstructing the circumstaces of traffic accidents. We propose a novel method for reconstructing the trajectory of vehicles from drive recorder images and a point cloud around the road. First, we apply ORB-SLAM to image sequence of the drive recorder for obtaining the vehicle pose trajectory; however this is based on relative coordinates and a relative scale. For estimating the absolute coordinates and scale of the trajectory, which cannot be obtained from a monocular SLAM like ORB-SLAM, we match the feature points detected in the image sequence with the three-dimensional (3D) point cloud of surrounding environment. For finding 3D points matching the feature points, we generate candidate images by the rendering 3D point cloud of the surrounding environment using the position initially estimated by the Global Positioning System (GPS). Next, we match to obtain the 3D two-dimensional (2D) generated images and drive recorder image to get 3D-2D point correspondences between the 3D point cloud and the drive recorder images; thus, we can convert the relative estimation of the camera pose by ORB-SLAM to the coordinates of the 3D point cloud of the surrounding environment. In the evaluation experiments, we confirmed the effectiveness of our method by comparing the vehicle poses estimated by our method, with those of RTKGPS, which exhibits high measurement precision.

元の言語English
ページ(範囲)2371-2376
ページ数6
ジャーナルIS and T International Symposium on Electronic Imaging Science and Technology
Part F138660
DOI
出版物ステータスPublished - 2018 1 1
イベントIntelligent Robotics and Industrial Applications using Computer Vision 2018, IRIACV 2018 - Burlingame, United States
継続期間: 2018 1 282018 2 1

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

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