2020/02/23 by Haoyang Ye, Ye, Haoyang, Huaiyang Huang +3
Computer Science · Earth and Planetary Sciences · Engineering · #3D Surveying and Cultural Heritage #Advanced Vision and Imaging #Artificial intelligence #Computer Vision and Pattern Recognition (cs.CV) #Computer graphics (images) #Computer science #Computer vision #FOS: Computer and information sciences #Global Map #Graph #Mobile robot #Monocular #Planar #Rendering (computer graphics) #Robot #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Simultaneous localization and mapping #Vertex (graph theory) #cs.CV #cs.RO
paper · pdf · doi:10.48550/arxiv.2002.09923
7 pages, 6 figures, to appear in ICRA 2020
arxiv created 2020/02/23 · openalex publication_date 2020/02/23 · arxiv updated 2020/02/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we introduce an approach to tracking the pose of a monocular camera in a prior surfel map. By rendering vertex and normal maps from the prior surfel map, the global planar information for the sparse tracked points in the image frame is obtained. The tracked points with and without the global planar information involve both global and local constraints of frames to the system. Our approach formulates all constraints in the form of direct photometric errors within a local window of the frames. The final optimization utilizes these constraints to provide the accurate estimation of global 6-DoF camera poses with the absolute scale. The extensive simulation and real-world experiments demonstrate that our monocular method can provide accurate camera localization results under various conditions.