Virtual view synthesis with heuristic spatial motion

Wenfeng Li, Baoxin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Probabilistic methods have been used in image-based rendering for solving the virtual view synthesis problem with Bayesian inference. To work well, the inference process requires the input views to be consistent to yield reasonable result, which in turn constrains the cameras to be very close to each other. Many approaches to relieving such constraint focus on the prior model. In this paper, we present a method which treats the virtual view as the outcome of a spatial motion from one real view. A sequence of images is generated heuristically to preserve textures with the aid of steerable filters. Interim results are further refined with texture-based Markov random field prior model. Experiments show that the synthesized view can have satisfactory image quality with only a few input images from wide baseline cameras.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages1508-1511
Number of pages4
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: Oct 12 2008Oct 15 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2008 IEEE International Conference on Image Processing, ICIP 2008
CountryUnited States
CitySan Diego, CA
Period10/12/0810/15/08

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Keywords

  • Bayesian inference
  • Image-based rendering
  • Motion
  • Virtual view synthesis

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Li, W., & Li, B. (2008). Virtual view synthesis with heuristic spatial motion. In 2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings (pp. 1508-1511). [4712053] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2008.4712053