Monocular camera localization in 3D LiDAR maps
| Autor: | Tim Caselitz, Bastian Steder, Wolfram Burgard, Michael Ruhnke |
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| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Camera matrix Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Bundle adjustment 02 engineering and technology Iterative reconstruction Simultaneous localization and mapping 020901 industrial engineering & automation Lidar Camera auto-calibration Feature (computer vision) Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Visual odometry Image sensor business Camera resectioning |
| Zdroj: | IROS |
| DOI: | 10.1109/iros.2016.7759304 |
| Popis: | Localizing a camera in a given map is essential for vision-based navigation. In contrast to common methods for visual localization that use maps acquired with cameras, we propose a novel approach, which tracks the pose of monocular camera with respect to a given 3D LiDAR map. We employ a visual odometry system based on local bundle adjustment to reconstruct a sparse set of 3D points from image features. These points are continuously matched against the map to track the camera pose in an online fashion. Our approach to visual localization has several advantages. Since it only relies on matching geometry, it is robust to changes in the photometric appearance of the environment. Utilizing panoramic LiDAR maps additionally provides viewpoint invariance. Yet low-cost and lightweight camera sensors are used for tracking. We present real-world experiments demonstrating that our method accurately estimates the 6-DoF camera pose over long trajectories and under varying conditions. |
| Databáze: | OpenAIRE |
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