By Topic

Plenoptic Layer-Based Modeling for Image Based Rendering

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
James Pearson ; Department of Electrical and Electronic Engineering, Imperial College, London, U.K. ; Mike Brookes ; Pier Luigi Dragotti

Image based rendering is an attractive alternative to model based rendering for generating novel views because of its lower complexity and potential for photo-realistic results. To reduce the number of images necessary for alias-free rendering, some geometric information for the 3D scene is normally necessary. In this paper, we present a fast automatic layer-based method for synthesizing an arbitrary new view of a scene from a set of existing views. Our algorithm takes advantage of the knowledge of the typical structure of multiview data to perform occlusion-aware layer extraction. In addition, the number of depth layers used to approximate the geometry of the scene is chosen based on plenoptic sampling theory with the layers placed non-uniformly to account for the scene distribution. The rendering is achieved using a probabilistic interpolation approach and by extracting the depth layer information on a small number of key images. Numerical results demonstrate that the algorithm is fast and yet is only 0.25 dB away from the ideal performance achieved with the ground-truth knowledge of the 3D geometry of the scene of interest. This indicates that there are measurable benefits from following the predictions of plenoptic theory and that they remain true when translated into a practical system for real world data.

Published in:

IEEE Transactions on Image Processing  (Volume:22 ,  Issue: 9 )