DocumentCode
3421916
Title
Depth from Combining Defocus and Correspondence Using Light-Field Cameras
Author
Tao, Michael W. ; Hadap, Sunil ; Malik, Jagannath ; Ramamoorthi, Ravi
Author_Institution
Univ. of California, Berkeley, Berkeley, CA, USA
fYear
2013
fDate
1-8 Dec. 2013
Firstpage
673
Lastpage
680
Abstract
Light-field cameras have recently become available to the consumer market. An array of micro-lenses captures enough information that one can refocus images after acquisition, as well as shift one´s viewpoint within the sub-apertures of the main lens, effectively obtaining multiple views. Thus, depth cues from both defocus and correspondence are available simultaneously in a single capture. Previously, defocus could be achieved only through multiple image exposures focused at different depths, while correspondence cues needed multiple exposures at different viewpoints or multiple cameras, moreover, both cues could not easily be obtained together. In this paper, we present a novel simple and principled algorithm that computes dense depth estimation by combining both defocus and correspondence depth cues. We analyze the x-u 2D epipolar image (EPI), where by convention we assume the spatial x coordinate is horizontal and the angular u coordinate is vertical (our final algorithm uses the full 4D EPI). We show that defocus depth cues are obtained by computing the horizontal (spatial) variance after vertical (angular) integration, and correspondence depth cues by computing the vertical (angular) variance. We then show how to combine the two cues into a high quality depth map, suitable for computer vision applications such as matting, full control of depth-of-field, and surface reconstruction.
Keywords
cameras; computer vision; microlenses; computer vision application; correspondence depth cue; defocus depth cue; dense depth estimation; depth-of-field control; full-4D EPI; high-quality depth map; horizontal spatial coordinate; horizontal variance; image refocus; lens subapertures; light-field cameras; matting; microlens array; multiple-image exposure; surface reconstruction; vertical angular coordinate; vertical integration; vertical variance; viewpoint shift; x-u 2D epipolar image; Apertures; Cameras; Estimation; Lenses; Noise measurement; Robustness; Three-dimensional displays;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location
Sydney, NSW
ISSN
1550-5499
Type
conf
DOI
10.1109/ICCV.2013.89
Filename
6751193
Link To Document