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Geometry and Texture from Thousands of Images

  • J.P. Mellor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2018)

Abstract

This paper presents a novel method for automatically recovering dense surface patches using large sets (1000’s) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Some of the most important characteristics of our approach are that it: 1) uses and refines noisy calibration estimates; 2) compensates for large variations in illumination; 3) tolerates significant soft occlusion (e.g. tree branches); and 4) associates, at a fundamental level, an estimated normal (eliminating the frontal-planar assumption) and texture with each surface patch.

Keywords

Global Position System Global Position System Geometric Constraint Camera Calibration Surface Patch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • J.P. Mellor
    • 1
  1. 1.Rose-Hulman Institute of TechnologyIN

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