Paper Info
Title
Texture optimization for seamless view synthesis through energy minimization
Abstract
In this paper, we present a view synthesis method named Visto which aims to generate seamless novel views from a monocular view input. We formulate the problem as joint optimization of inter-view texture similarity and geometry preservation, which significantly differs from traditional view synthesis framework. In this way, the image characteristics of virtual view are inherently inherited from the reference view without introducing any image prior or texture modeling technique. The energy function is minimized using Gauss-Seidel-like approach, and the quality of the virtual view is refined iteratively. The proposed approach also tolerates small depth map errors. Further more, the algorithm is parallel friendly. The simulation results outperform several existing state-of-the-art monocular view synthesis systems.
Year
DOI
Venue
2012
10.1145/2393347.2396299
ACM Multimedia 2001
Keywords
Field
DocType
synthesis system,existing state-of-the-art monocular view,reference view,gauss-seidel-like approach,image characteristic,view synthesis method,seamless novel view,monocular view input,traditional view synthesis framework,energy minimization,seamless view synthesis,texture optimization,virtual view
Computer vision,Computer science,View synthesis,Texture modeling,Artificial intelligence,Depth map,Monocular,Energy minimization
Conference
Citations 
PageRank 
References 
2
0.37
9
Authors
6
Name
Order
Citations
PageRank
Wenxiu Sun116020.79
Oscar C. Au21592176.54
Lingfeng Xu3539.81
Yujun Li410418.20
Wei Hu524422.01
Zhiding Yu642130.08