Depth Super-Resolution Meets Uncalibrated Photometric Stereo
Peng S, Haefner B, Queau Y, Cremers D (2017)
Publication Type: Conference contribution
Publication year: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2018-January
Pages Range: 2961-2968
Conference Proceedings Title: Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Event location: Venice, ITA
ISBN: 9781538610343
Abstract
A novel depth super-resolution approach for RGB-D sensors is presented. It disambiguates depth super-resolution through high-resolution photometric clues and, symmetrically, it disambiguates uncalibrated photometric stereo through low-resolution depth cues. To this end, an RGB-D sequence is acquired from the same viewing angle, while illuminating the scene from various uncalibrated directions. This sequence is handled by a variational framework which fits high-resolution shape and reflectance, as well as lighting, to both the low-resolution depth measurements and the high-resolution RGB ones. The key novelty consists in a new PDE-based photometric stereo regularizer which implicitly ensures surface regularity. This allows to carry out depth super-resolution in a purely data-driven manner, without the need for any ad-hoc prior or material calibration. Real-world experiments are carried out using an out-of-the-box RGB-D sensor and a hand-held LED light source.
Involved external institutions
Germany (DE)How to cite
APA:
Peng, S., Haefner, B., Queau, Y., & Cremers, D. (2017). Depth Super-Resolution Meets Uncalibrated Photometric Stereo. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 (pp. 2961-2968). Venice, ITA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Peng, Songyou, et al. "Depth Super-Resolution Meets Uncalibrated Photometric Stereo." Proceedings of the 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017, Venice, ITA Institute of Electrical and Electronics Engineers Inc., 2017. 2961-2968.
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