Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Inferring 3D Scene Structure from a Single Polarization Image
 

Summary: Inferring 3D Scene Structure
from a Single Polarization Image
S. Rahmann
Institute for Pattern Recognition and Image Processing, Computer Science Department
Albert-Ludwigs-University of Freiburg, Freiburg, Germany
ABSTRACT
This paper presents a method for deducing both, the 3D orientation of a at, rough surface and the 3D position of
the light source by analysing the specular re ection produced by the light source on the surface. This is achieved
by polarization analysis of the re ected light from a single point of view. This new approach is applicable to all
materials and to all isotropic surface structures excluding mirror like and ideal Lambertian surfaces; therefore, it can
be applied in most cases of practical interest. First the paper shows that important 3D information of the position
of the light source can be inferred by polarization analysis. Second we present a new method for the calculation of
surface orientation which can be deduced from the intensity image of a re ected point light source. Furthermore the
paper shows the bene t to be derived from the combination of the two former results. In the resulting algorithm
the complete 3D information of the light source and the re ecting surface can be inferred. The applicability under
di erent lighting conditions is demonstrated. In contrast to previous results our method does not need any calibration
of the experimental setup.
Keywords: Polarization Analysis, Physics-Based-Vision, Specular Re ection, Highlight Analysis
1. INTRODUCTION
The term polarization image was rst used by Wol . 1 In contrast to an intensity image a polarization image encodes

  

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

 

Collections: Computer Technologies and Information Sciences