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Shape and View Independent Reflectance Map from Multiple Views
 

Summary: Shape and View Independent Reflectance Map
from Multiple Views
Tianli Yu, Ning Xu, and Narendra Ahuja
Beckman Institute & Electrical and Computer Engineering Department
University of Illinois at Urbana-Champaign, Urbana IL 61801, USA
{tianli, ningxu, ahuja}@vision.ai.uiuc.edu
Abstract. We consider the problem of estimating the 3D shape and
reflectance properties of an object made of a single material from a
calibrated set of multiple views. To model reflectance, we propose a
View Independent Reflectance Map (VIRM) and derive it from Torrance-
Sparrow BRDF model. Reflectance estimation then amounts to estimat-
ing VIRM parameters. We represent object shape using surface trian-
gulation. We pose the estimation problem as one of minimizing cost of
matching input images, and the images synthesized using shape and re-
flectance estimates. We show that by enforcing a constant value of VIRM
as a global constraint, we can minimize the matching cost function by
iterating between VIRM and shape estimation. Experiment results on
both synthetic and real objects show that our algorithm is effective in re-
covering the 3D shape as well as non-lambertian reflectance information.
Our algorithm does not require that light sources be known or calibrated

  

Source: Ahuja, Narendra - Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign

 

Collections: Computer Technologies and Information Sciences; Engineering