DocumentCode :
1798915
Title :
Depth map estimation in light fields using an stereo-like taxonomy
Author :
Calderon, Francisco C. ; Parra, Carlos A. ; Nino, Cesar L.
Author_Institution :
Fac. de Ing. Electron., Pontificia Univ. Javeriana, Bogota, Colombia
fYear :
2014
fDate :
17-19 Sept. 2014
Firstpage :
1
Lastpage :
5
Abstract :
The light field or LF is a function that describes the amount of light traveling in every direction (angular) through every point (spatial) in a scene, this LF can be captured in several ways, using arrays of cameras, or more recently using a single camera with an special lens, that allows the capture of angular and spatial information of light rays of a scene (LF). This recent camera implementation gives a different approach to find the dept of a scene using only a single camera. In order to estimate the depth, we describe a taxonomy, similar to the one used in stereo Depth-map algorithms. That consist in the creation of a cost tensor to represent the matching cost between different disparities, then, using a support weight window, aggregate the cost tensor, finally, using a winner-takes-all optimization algorithm, search for the best disparities. This paper explains in detail the several changes made to an stereo-like taxonomy, to be applied in a light field, and evaluate this algorithm using a recent database that for the first time, provides several ground-truth light fields, with a respective ground-truth depth map.
Keywords :
cameras; feature extraction; image processing; image sensors; lenses; optimisation; spatial variables measurement; angular information; cost tensor; depth map estimation; lens; light fields; optimization algorithm; single camera; spatial information; stereo depth-map algorithms; stereo-like taxonomy; support weight window; Cameras; Computer vision; Equations; Estimation; Mathematical model; Stereo vision; Taxonomy; Depth Map; Stereo Light field; Stereo Taxonomy; smoothing filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image, Signal Processing and Artificial Vision (STSIVA), 2014 XIX Symposium on
Conference_Location :
Armenia
Type :
conf
DOI :
10.1109/STSIVA.2014.7010131
Filename :
7010131
Link To Document :
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