BMVC 2004, Kingston, 7th-9th Sept, 2004
EigenFairing: 3D Model Fairing using Image Coherence
P. Mishra, O. Amidi, and T. Kanade (Carnegie Mellon University, USA)
A surface is often modeled as a triangulated mesh of 3D points and textures
associated with faces of the mesh. The 3D points could be either sampled
from range data or derived from a set of images using a stereo or Structurefrom-
Motion algorithm. When the points do not lie at critical points of maximum
curvature or discontinuities of the real surface, faces of the mesh do
not lie close to the modeled surface. This results in textural artifacts, and the
model is not perfectly coherent with a set of actual images�the ones that are
used to texture-map its mesh.
This paper presents a technique for perfecting the 3D surface model by
repositioning its vertices so that it is coherent with a set of observed images
of the object. The textural artifacts and incoherence with images are due to
the non-planarity of a surface patch being approximated by a planar face,
as observed from multiple viewpoints. Image areas from the viewpoints are
used to represent texture for the patch in eigenspace. The eigenspace representation
captures variations of texture, which we seek to minimize.
A coherence measure based on the difference between the face textures
reconstructed from eigenspace and the actual images is used to reposition the
vertices so that the model is improved or faired. We refer to this technique
of model refinement as EigenFairing, by which the model is faired, both geometrically
and texturally, to better approximate the real surface.