|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
RECONSTRUCTING RELIEF SURFACES.
G. Vogiatzis, P.H.S. Torr, S. Seitz and R. Cipolla.
This paper generalizes Markov Random Field (MRF) stereo methods to the generation of surface relief (height) fields rather than disparity or depth maps. This generalization enables the reconstruction of complete object models using the same algorithms that have been previously used to compute depth maps in binocular stereo. In contrast to traditional dense stereo where the parametrization is image based, here we advocate a parametrization by a height field over any base surface. In practice, the base surface is a coarse approximation to the true geometry, e.g., a bounding box, visual hull or triangulation of sparse correspondences, and is assigned or computed using other means. A dense set of sample points is defined on the base surface, each with a fixed normal direction and unknown height value. The estimation of heights for the sample points is achieved by a belief propagation technique. Our method provides a viewpoint independent smoothness constraint, a more compact parametrization and explicit handling of occlusions. We present experimental results on real scenes as well as a quantitative evaluation on an artificial scene.
If you have difficulty viewing files that end
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
If you have difficulty viewing files that are in PostScript, (ending
'.ps.gz'), then you may be able to
find tools to view them at
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.
|| Search | CUED | Cambridge University ||
2005 Cambridge University Engineering Dept
Information provided by milab-maintainer