Recovering shape and reflectance model of non-lambertian objects from multiple views

Tianli Yu, Ning Xu, Narendra Ahuja

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes an algorithm to simultaneously estimate both the 3D shape and parameters of a surface reflectance model from multiple views of an object made of a single material. The algorithm is based on a multiple view shape from shading method. The shape of the object is represented by a triangular mesh. The Phong reflectance model is used to model the surface reflectance. We iteratively find the shape and reflectance parameters that best fit all input images. The estimates of shape and reflectance model are gradually refined by subdividing triangles in the mesh into smaller ones. The estimation takes into account both self-occlusion and self-shadowing. Analysis shows that the accuracy of reflectance estimation is limited by the triangle size in the shape model. We also propose to use Richardson extrapolation to overcome this and further refine the reflectance model estimate. The estimated 3D shape and reflectance model can be used to render the same object from different viewing directions and under different lighting conditions. Experimental results on both synthetic and real objects are given.

Original languageEnglish (US)
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2
StatePublished - 2004

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Software
  • Control and Systems Engineering

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