Multi-scale Direct Sparse Visual Odometry for Large-Scale Natural Environment

• Main Authors: Wu, Xiaolong, Pradalier, Cédric
• Other Authors: Georgia Tech Lorraine Metz, Ecole Nationale Supérieure des Arts et Metiers Metz-Georgia Institute of Technology Atlanta -Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2018
• Subjects: Image reconstruction; Cameras; Optimization; Three-dimensional displays; Real-time systems; Tracking; Simultaneous localization and mapping; [INFO]Computer Science [cs]; Devon Island
• Online Access: https://hal.science/hal-02278006

International audience In this paper, we describe a multi-scale monocular direct sparse visual odometry (DSO) system to recover large-scale trajectories in unstructured natural environments in real time, while building a consistent metric map of the visited scenes. In contrast to the current state-o...