Towards a benchmark for RGB-D SLAM evaluation - Archive ouverte HAL
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Communication Dans Un Congrès Année : 2011
Towards a benchmark for RGB-D SLAM evaluation
Jürgen Sturm (1) , Stéphane Magnenat (2) , Nikolas Engelhard (3) , François Pomerleau (2) , Francis Colas (2) , Daniel Cremers (1) , Roland Siegwart (2) , Wolfram Burgard (3)
1 CVPR - Computer Vision and Pattern Recognition Group [Münster] (Computer Vision and Pattern Recognition Group Einsteinstraße 62 48149 Münster - Allemagne)
"> CVPR - Computer Vision and Pattern Recognition Group [Münster]
2 ASL - Autonomous Systems Lab (Autonomous Systems Lab Institute of Robotics and Intelligent Systems ETH Zentrum, CLA E 31 Tannenstrasse 3 CH-8092 Zürich - Suisse)
"> ASL - Autonomous Systems Lab
3 Department of Computer Science [Freiburg] (Georges-Kohler-Allee 79, 79108 Freiburg, Germany - Allemagne)
"> Department of Computer Science [Freiburg]

Résumé

We provide a large dataset containing RGB-D image sequences and the ground-truth camera trajectories with the goal to establish a benchmark for the evaluation of visual SLAM systems. Our dataset contains the color and depth images of a Microsoft Kinect sensor and the ground-truth trajectory of camera poses. The data was recorded at full frame rate (30 Hz) and sensor resolution (640x480). The ground-truth trajectory was obtained from a high-accuracy motion-capture system with eight high-speed tracking cameras (100 Hz). Further, we provide the accelerometer data from the Kinect. Finally, we propose an evaluation criterion for measuring the quality of the estimated camera trajectory of visual SLAM systems.

Domaines

Robotique [cs.RO]
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https://hal.science/hal-01142608

Soumis le : mercredi 15 avril 2015-15:38:34

Dernière modification le : lundi 23 septembre 2024-10:28:31

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Dates et versions

hal-01142608 , version 1 (15-04-2015)
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  • HAL Id : hal-01142608 , version 1

Citer

Jürgen Sturm, Stéphane Magnenat, Nikolas Engelhard, François Pomerleau, Francis Colas, et al.. Towards a benchmark for RGB-D SLAM evaluation. RGB-D Workshop on Advanced Reasoning with Depth Cameras at Robotics: Science and Systems Conf.(RSS), 2011, Los Angeles, United States. ⟨hal-01142608⟩

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