Rolling shutter and motion blur removal for depth cameras
2016 (English)In: Proceedings - IEEE International Conference on Robotics and Automation, IEEE conference proceedings, 2016, 5098-5105 p.Conference paper (Refereed)
Structured light range sensors (SLRS) like the Microsoft Kinect have electronic rolling shutters (ERS). The output of such a sensor while in motion is subject to significant motion blur (MB) and rolling shutter (RS) distortion. Most robotic literature still does not explicitly model this distortion, resulting in inaccurate camera motion estimation. In RGBD cameras, we show via experimentation that the distortion undergone by depth images is different from that of color images and provide a mathematical model for it. We propose an algorithm that rectifies for these RS and MB distortions. To assess the performance of the algorithm we conduct an extensive set of experiments for each step of the pipeline. We assess the performance of our algorithm by comparing the performance of the rectified images on scene-flow and camera pose estimation, and show that with our proposed rectification, the performance improvement is significant.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2016. 5098-5105 p.
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:kth:diva-197237DOI: 10.1109/ICRA.2016.7487715ISI: 000389516204051ScopusID: 2-s2.0-84977527878ISBN: 9781467380263OAI: oai:DiVA.org:kth-197237DiVA: diva2:1052712
2016 IEEE International Conference on Robotics and Automation, ICRA 2016, 16 May 2016 through 21 May 2016
QC 201612072016-12-072016-11-302017-01-19Bibliographically approved