Towards Full 3D Helmholtz Stereovision Algorithms

Helmholtz stereovision methods are limited to binocular stereovision or depth maps reconstruction. In this paper, we extend these methods to recover the full 3D shape of the objects of a scene from multiview Helmholtz stereopsis. Thus, we are able to reconstruct the complete three-dimensional shape of objects made of any arbitrary and unknown bidirectional reflectance distribution function. Unlike previous methods, this can be achieved using a full surface representation model. In particular occlusions (self occlusions as well as cast shadows) are easier to handle in the surface optimization process. More precisely, we use a triangular mesh representation which allows to naturally specify relationships between the geometry of a point of the scene and its surface normal. We show how to implement the presented approach using a coherent gradient descent flow. Results and benefits are illustrated on various examples.

@InProceedings\{DPB10,
  author       = "Delaunoy, Ama{\"e}l and Prados, Emmanuel and Belhumeur, Peter",
  title        = "Towards Full 3D Helmholtz Stereovision Algorithms",
  booktitle    = "Proceedings of the 10th Asian Conference on Computer Vision, Queenstown, New-Zealand",
  series       = "Lecture Notes in Computer Science",
  month        = "nov",
  year         = "2010",
  publisher    = "Springer",
  organization = "ACCV",
  url          = "http://perception.inrialpes.fr/Publications/2010/DPB10"
}