Defocus Deblurring and Superresolution for Time-of-Flight Depth Cameras
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Type
Conference PaperAuthors
Xiao, LeiHeide, Felix
O'Toole, Matthew
Kolb, Andreas
Hullin, Matthias B.
Kutulakos, Kyros
Heidrich, Wolfgang
Date
2015-10-15Online Publication Date
2015-10-15Print Publication Date
2015-06Permanent link to this record
http://hdl.handle.net/10754/556519
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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.Citation
Lei Xiao, Heide, F., O’Toole, M., Kolb, A., Hullin, M. B., Kutulakos, K., & Heidrich, W. (2015). Defocus deblurring and superresolution for time-of-flight depth cameras. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr.2015.7298851Conference/Event name
Computer Vision and Pattern Recognition (CVPR),2015Additional Links
http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Xiao_Defocus_Deblurring_and_2015_CVPR_paper.pdfae974a485f413a2113503eed53cd6c53
10.1109/CVPR.2015.7298851