Dense continuous-time tracking and mapping with rolling shutter RGB-D cameras
Kerl C, Stueckler J, Cremers D (2015)
Publication Type: Conference contribution
Publication year: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2015 International Conference on Computer Vision, ICCV 2015
Pages Range: 2264-2272
Conference Proceedings Title: Proceedings of the IEEE International Conference on Computer Vision
Event location: Santiago, CHL
ISBN: 9781467383912
Abstract
We propose a dense continuous-time tracking and mapping method for RGB-D cameras. We parametrize the camera trajectory using continuous B-splines and optimize the trajectory through dense, direct image alignment. Our method also directly models rolling shutter in both RGB and depth images within the optimization, which improves tracking and reconstruction quality for low-cost CMOS sensors. Using a continuous trajectory representation has a number of advantages over a discrete-time representation (e.g. camera poses at the frame interval). With splines, less variables need to be optimized than with a discrete representation, since the trajectory can be represented with fewer control points than frames. Splines also naturally include smoothness constraints on derivatives of the trajectory estimate. Finally, the continuous trajectory representation allows to compensate for rolling shutter effects, since a pose estimate is available at any exposure time of an image. Our approach demonstrates superior quality in tracking and reconstruction compared to approaches with discrete-time or global shutter assumptions.
Involved external institutions
Germany (DE)How to cite
APA:
Kerl, C., Stueckler, J., & Cremers, D. (2015). Dense continuous-time tracking and mapping with rolling shutter RGB-D cameras. In Proceedings of the IEEE International Conference on Computer Vision (pp. 2264-2272). Santiago, CHL: Institute of Electrical and Electronics Engineers Inc..
MLA:
Kerl, Christian, Joerg Stueckler, and Daniel Cremers. "Dense continuous-time tracking and mapping with rolling shutter RGB-D cameras." Proceedings of the 15th IEEE International Conference on Computer Vision, ICCV 2015, Santiago, CHL Institute of Electrical and Electronics Engineers Inc., 2015. 2264-2272.
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