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Stereo Correspondence Evaluation Methods: A Systematic Review

  • Camilo VargasEmail author
  • Ivan Cabezas
  • John W. Branch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9475)

Abstract

The stereo correspondence problem has received significant attention in literature during approximately three decades. During that period of time, the development on stereo matching algorithms has been quite considerable. In contrast, the proposals on evaluation methods for stereo matching algorithms are not so many. This is not trivial issue, since an objective assessment of algorithms is required not only to measure improvements on the area, but also to properly identify where the gaps really are, and consequently, guiding the research. In this paper, a systematic review on evaluation methods for stereo matching algorithms is presented. The contributions are not only on the found results, but also on how it is explained and presented: aiming to be useful for the researching community on visual computing, in which such systematic review process is not yet broadly adopted.

Keywords

Stereo Image Stereo Correspondence Stereo Match Algorithm Disparity Gradient Prediction Error Method 
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 International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Departamento de Ciencias de la Computación Y de la Decisión, Facultad de MinasUniversidad Nacional de Colombia.BogotáColombia
  2. 2.Laboratorio de Investigación para el Desarrollo de la Ingeniería de SoftwareUniversidad de San BuenaventuraCaliColombia

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