Paper Info
Title
Bayesian Depth Map Interpolation Using Edge Driven Markov Random Fields
Abstract
In this work we present a Bayesian interpolation procedure to perform depth map up sampling. The depth map prior is designed via an edge driven Markov Random Field. The upsampling procedure is computationally efficient and outperforms selected state of the art upsampling procedure; moreover it allows to perform depth map upsampling even without the reference high resolution luminance map.
Year
Venue
DocType
2012
COMPUTATIONAL MODELLING OF OBJECTS REPRESENTED IN IMAGES: FUNDAMENTALS, METHODS AND APPLICATIONS III
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Stefania Colonnese113726.43
Stefano Rinauro2508.72
Gaetano Scarano320931.32