Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

D. Kurz, S. Lieberknecht, S. Benhimane
Benchmarking Inertial Sensor-Aided Localization and Tracking Methods
The 2nd International Workshop on AR/MR Registration, Tracking and Benchmarking (TrakMark2011?), Basel, Switzerland, Oct. 25, 2011 (bib)

This paper investigates means to benchmark methods for camera pose localization and tracking that in addition to a camera image make use of inertial sensor measurements. In particular the direction of the gravity has recently shown to provide useful information to aid vision-based approaches making them outperform visiononly methods. Obviously, it is desirable to benchmark the performance of such methods and to compare them with state-of-the-art approaches, but to the best of our knowledge, all publicly available benchmarking datasets unfortunately lack gravity information. We present different simple means to generate one.s own benchmarks for inertial sensor-aided localization and tracking methods and most considerably show how existing datasets, that do not have inertial sensor data, can be exploited. We demonstrate how to evaluate Gravity-Aligned Feature Descriptors (GAFD) and Gravity-Rectified Feature Descriptors (GREFD) on an existing benchmark dataset with ground truth poses. By synthesizing gravity measurements from these poses we achieve similar results to using real sensor measurements at significantly less effort. Most importantly, the proposed procedure enables the comparison with existing evaluation results on the same data. The paper concludes with a requirements analysis and suggestions for the design of future benchmarking datasets for localization and tracking methods.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif