DocumentCode :
3278109
Title :
Image completion for view synthesis using Markov random fields and efficient belief propagation
Author :
Habigt, Julian ; Diepold, Klaus
Author_Institution :
Inst. for Data Process., Tech. Univ. Munchen, Munich, Germany
fYear :
2013
fDate :
15-18 Sept. 2013
Firstpage :
2131
Lastpage :
2134
Abstract :
View synthesis is a process for generating novel views from a scene which has been recorded with a 3-D camera setup. It has important applications in 3-D post-production and 2-D to 3-D conversion. However, a central problem in the generation of novel views lies in the handling of disocclusions. Background content, which was occluded in the original view, may become unveiled in the synthesized view. This leads to missing information in the generated view which has to be filled in a visually plausible manner. We present an inpainting algorithm for disocclusion filling in synthesized views based on Markov random fields and efficient belief propagation. We compare the result to two state-of-the-art algorithms and demonstrate a significant improvement in image quality.
Keywords :
Markov processes; rendering (computer graphics); 2D conversion; 3D camera setup; 3D conversion; 3D post-production; Markov random fields; belief propagation; central problem; disocclusion filling; image completion; image quality; inpainting algorithm; synthesized views; view synthesis; DIBR; Hole-Filling; Inpainting; MRF; View Synthesis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
Type :
conf
DOI :
10.1109/ICIP.2013.6738439
Filename :
6738439
Link To Document :
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