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ITERATIVE 3D SURFACE MODELLING FROM A SPARSE SET OF MATCHED FEATURE and Narendra Ahuja
 

Summary: ITERATIVE 3D SURFACE MODELLING FROM A SPARSE SET OF MATCHED FEATURE
POINTS
Ning Xu
and Narendra Ahuja
Beckman Institute and ECE Department
University of Illinois at Urbana-Champaign
{ningxu,ahuja}@vision.ai.uiuc.edu
ABSTRACT
We present an iterative algorithm to reconstruct a 3D
object surface from a sparse set of matched feature points
on the input stereo images of the object. The initial matches
are sparse and do not have to be accurate. The reconstructed
3D surface is represented in terms of triangular polygons
whose vertices are initially the 3D points corresponding to
these matched feature points. In order to render photorealis-
tic images of the surface, these feature points are iteratively
updated. New feature points are added into the feature point
set as well as the depth estimates of the feature points are re-
fined. Experimental results showing the updated correspon-
dences, reconstructed surfaces and virtual views rendered

  

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

 

Collections: Computer Technologies and Information Sciences; Engineering