Title :
Continuous depth map reconstruction from light fields
Author :
Jianqiao Li ; Ze-Nian Li
Author_Institution :
Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
Abstract :
Light field analysis recently received growing interest, since its rich structure information benefits many computer vision tasks. This paper presents a novel method to reconstruct continuous depth maps from light field data. Conventional approaches usually treat depth map reconstruction as an optimization problem with discrete labels. On the contrary, our proposed method can obtain continuous depth maps by solving a linear system, which preserves richer details compared with conventional discrete approaches. Structure tensor is employed to extract raw depth information and corresponding confidence levels from the light field data. We introduce a method to reduce the adverse effect of unreliable local estimations, which helps to get rid of errors in specular areas and edges where depth values are discontinuous. Experiments on both synthetic and real light field data demonstrate the effectiveness of the proposed method.
Keywords :
computer vision; estimation theory; image reconstruction; optimisation; computer vision; continuous depth map reconstruction; light field analysis; linear system; local estimation; optimization problem; structure tensor; Computer vision; Estimation; Image color analysis; Image reconstruction; Linear systems; Sparse matrices; Tensile stress; Depth map reconstruction; light field; linear system;
Conference_Titel :
Multimedia and Expo (ICME), 2013 IEEE International Conference on
Conference_Location :
San Jose, CA
DOI :
10.1109/ICME.2013.6607557