Depth superresolution using motion adaptive regularization

  • Ulugbek S. Kamilov
  • , Petros T. Boufounos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Spatial resolution of depth sensors is often significantly lower compared to that of conventional optical cameras. Recent work has explored the idea of improving the resolution of depth using higher resolution intensity as a side information. In this paper, we demonstrate that further incorporating temporal information in videos can significantly improve the results. In particular, we propose a novel approach that improves depth resolution, exploiting the space-time redundancy in the depth and intensity using motion-adaptive low-rank regularization. Experiments confirm that the proposed approach substantially improves the quality of the estimated high-resolution depth. Our approach can be a first component in systems using vision techniques that rely on high resolution depth information.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509015528
DOIs
StatePublished - Sep 22 2016
Event2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016 - Seattle, United States
Duration: Jul 11 2016Jul 15 2016

Publication series

Name2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016

Conference

Conference2016 IEEE International Conference on Multimedia and Expo Workshop, ICMEW 2016
Country/TerritoryUnited States
CitySeattle
Period07/11/1607/15/16

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