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Accurate Depth Map Estimation from a Lenslet Light field Camera



Abstract

This paper introduces an algorithm to estimate accurate depth map from a lenslet light field camera. Our algorithm estimates multi-view stereo correspondences at sub-pixel accuracy using a cost volume. Our key idea to build accurate costs is threefold.

First, sub-aperture images are displaced using the phase shift theorem. Second, gradient costs are adaptively aggregated using the angular coordinate of the light field. Third, feature correspondences between the sub-aperture images are utilized as an additional constraint. With the cost volume, a multi-label optimization propagates and corrects depth map at weak texture regions. Finally, we iteratively refine local depth map by fitting local quadratic function to estimate a non-discrete depth map. Since a micro-lens image contains unexpected distortions, we also present a method to correct the error. The effectiveness of our algorithm is demonstrated through challenging real world examples, with comparisons to the performance of state-of-the-art depth estimation algorithms.



What's new!!
14/07/07    We are going to present this work in ICVSS 2015 (Sicily, Italy)!!
14/05/15    We have uploaded dataset and source code (MATLAB 2014a Window version)!!
14/05/15    We are going to present this work in CVPR 2015 (Monday June 8, 3:30pm-6:00pm)


Accurate Depth Map Estimation from a Lenslet Light Field Camera
Hae-Gon Jeon, Jaesik Park, Gyeongmin Choe, Jinsun Park, Yunsu Bok, Yu-Wing Tai and In So Kweon
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2015


Related Link
Light-Field toolbox v.0.4 presented by Donald Dansereau.
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