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Robust Pixel Classification for 3D Modeling with Structured Light Yi Xu Daniel G. Aliaga
 

Summary: Robust Pixel Classification for 3D Modeling with Structured Light
Yi Xu Daniel G. Aliaga
Department of Computer Science
Purdue University
{xu43|aliaga}@cs.purdue.edu
ABSTRACT
Modeling 3D objects and scenes is an important part of computer
graphics. One approach to modeling is projecting binary patterns
onto the scene in order to obtain correspondences and reconstruct
a densely sampled 3D model. In such structured light systems,
determining whether a pixel is directly illuminated by the
projector is essential to decoding the patterns. In this paper, we
introduce a robust, efficient, and easy to implement pixel
classification algorithm for this purpose. Our method correctly
establishes the lower and upper bounds of the possible intensity
values of an illuminated pixel and of a non-illuminated pixel.
Based on the two intervals, our method classifies a pixel by
determining whether its intensity is within one interval and not in
the other. Experiments show that our method improves both the
quantity of decoded pixels and the quality of the final

  

Source: Aliaga, Daniel G. - Department of Computer Sciences, Purdue University

 

Collections: Computer Technologies and Information Sciences