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Characterization of Time-of-Flight Data

  • Miles HansardEmail author
  • Seungkyu Lee
  • Ouk Choi
  • Radu Horaud
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

This chapter introduces the principles and difficulties of time-of-flight depth measurement. The depth images that are produced by time-of-flight cameras suffer from characteristic problems, which are divided into the following two classes. First, there are systematic errors, such as noise and ambiguity, which are directly related to the sensor. Second, there are nonsystematic errors, such as scattering and motion blur, which are more strongly related to the scene content. It is shown that these errors are often quite different from those observed in ordinary color images. The case of motion blur, which is particularly problematic, is examined in detail. A practical methodology for investigating the performance of depth cameras is presented. Time-of-flight devices are compared to structured-light systems, and the problems posed by specular and translucent materials are investigated.

Keywords

Depth-cameras Time-of-Flight principle Motion blur Depth errors 

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Copyright information

© Miles Hansard 2013

Authors and Affiliations

  • Miles Hansard
    • 1
    Email author
  • Seungkyu Lee
    • 2
  • Ouk Choi
    • 2
  • Radu Horaud
    • 3
  1. 1.Electronic Engineering and Computer ScienceQueen Mary, University of LondonLondonUK
  2. 2.Samsung Advanced Institute of TechnologyYongin-siKorea, Republic of (South Korea)
  3. 3.INRIA Grenoble Rhône-AlpesMontbonnot Saint-MartinFrance

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