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Patch based synthesis for single depth image super-resolution

Mac Aodha, O; Campbell, NDF; Nair, A; Brostow, GJ; (2012) Patch based synthesis for single depth image super-resolution. In: Computer Vision – ECCV 2012. (pp. 71 -84). Springer-Verlag Berlin Heidelberg: Germany. Green open access

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Abstract

We present an algorithm to synthetically increase the resolution of a solitary depth image using only a generic database of local patches. Modern range sensors measure depths with non-Gaussian noise and at lower starting resolutions than typical visible-light cameras. While patch based approaches for upsampling intensity images continue to improve, this is the first exploration of patching for depth images. We match against the height field of each low resolution input depth patch, and search our database for a list of appropriate high resolution candidate patches. Selecting the right candidate at each location in the depth image is then posed as a Markov random field labeling problem. Our experiments also show how important further depth-specific processing, such as noise removal and correct patch normalization, dramatically improves our results. Perhaps surprisingly, even better results are achieved on a variety of real test scenes by providing our algorithm with only synthetic training depth data.

Type: Proceedings paper
Title: Patch based synthesis for single depth image super-resolution
Event: 12th European Conference on Computer Vision
ISBN-13: 9783642337116
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-642-33712-3_6
Publisher version: http://dx.doi.org/10.1007/978-3-642-33712-3_6
Language: English
Additional information: A. Fitzgibbon et al. (Eds.): ECCV 2012, Part III, LNCS 7574, pp. 71–84, 2012. © Springer-Verlag Berlin Heidelberg 2012
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1371091
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