Defocus Deblurring and Superresolution for Time-of-Flight Depth Cameras

Lei Xiao, Felix Heide, Matthew O'Toole, Andreas Kolb, Matthias B. Hullin, Kyros Kutulakos, Wolfgang Heidrich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

Continuous-wave time-of-flight (ToF) cameras show great promise as low-cost depth image sensors in mobile applications. However, they also suffer from several challenges, including limited illumination intensity, which mandates the use of large numerical aperture lenses, and thus results in a shallow depth of field, making it difficult to capture scenes with large variations in depth. Another shortcoming is the limited spatial resolution of currently available ToF sensors. In this paper we analyze the image formation model for blurred ToF images. By directly working with raw sensor measurements but regularizing the recovered depth and amplitude images, we are able to simultaneously deblur and super-resolve the output of ToF cameras. Our method outperforms existing methods on both synthetic and real datasets. In the future our algorithm should extend easily to cameras that do not follow the cosine model of continuous-wave sensors, as well as to multi-frequency or multi-phase imaging employed in more recent ToF cameras.
Original languageEnglish (US)
Title of host publicationThe IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2376-2384
Number of pages9
ISBN (Print)9781467369640
DOIs
StatePublished - Oct 15 2015

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