CoRBS: Comprehensive RGB-D Benchmark for SLAM using Kinect v2

CoRBS: Comprehensive RGB-D Benchmark for SLAM using Kinect v2
Oliver Wasenmüller, Marcel Meyer, Didier Stricker
IEEE Winter Conference on Applications of Computer Vision (WACV-2016), March 7-9, Lake Placid, NY, USA

In scientific evaluation public datasets and benchmarks are indispensable to perform objective assessment. In this paper we present a new Comprehensive RGB-D Benchmark for SLAM (CoRBS). In contrast to state-of-the-art RGB-D SLAM benchmarks, we provide the combination of real depth and color data together with a ground truth trajectory of the camera and a ground truth 3D model of the scene. Our novel benchmark allows for the first time to independently evaluate the localization as well as the mapping part of RGB-D SLAM systems with real data. We obtained the ground truth for the trajectory using an external motion capture system and for the scene geometry via an external 3D scanner, each with sub-millimeter precision. With precise calibration and systematic validation we ensured the high quality of CoRBS. Our dataset contains twenty image sequences of four different scenes captured with a Kinect v2. We provide all data in a global coordinate system to enable direct evaluation without any further alignment or calibration.
CoRBS, dataset, benchmark, SLAM, RGB-D, Kinect v2, geometry, trajectory