A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

We present a novel approach to the reconstruction of depth from light field data. Our method uses dictionary representations and group sparsity constraints to derive a convex formulation. Although our solution results in an increase of the problem dimensionality, we keep numerical complexity at bay by restricting the space of solutions and by exploiting an efficient Primal-Dual formulation. Comparisons with state of the art techniques, on both synthetic and real data, show promising performances.


Présenté à:
Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), Hong Kong, China
Année
2014
Mots-clefs:
Laboratoires:




 Notice créée le 2014-10-11, modifiée le 2019-03-17

Fichiers:
Télécharger le documentPDF
n/a:
Télécharger le documentPDF
Évaluer ce document:

Rate this document:
1
2
3
 
(Pas encore évalué)