Qualitative and quantitative evaluation of correlation based stereo matching algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate estimation of disparity is one of the most active research area in computer vision. In the last few decades numerous algorithms have been invented to find disparity precisely. However, these inventions throws problem in selecting most appropriate one for the required application. A detailed analysis is mandatory to solve this kind of problem. The main objective of this paper is to empirically evaluate a set of well known correlation based stereo matching algorithms. A qualitative and quantitative analysis results will be useful for selecting the most appropriate algorithm for the given application. The presented analysis is mainly focused on the evaluation of errors, robustness to change in illumination and the computation cost required for each algorithm.

Original languageEnglish
Title of host publicationAdvanced Computing, Networking and Security - International Conference, ADCONS 2011, Revised Selected Papers
Pages244-252
Number of pages9
Volume7135 LNCS
DOIs
Publication statusPublished - 2012
EventInternational Conference on Advanced Computing, Networking and Security, ADCONS 2011 - Surathkal, India
Duration: 16-12-201118-12-2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7135 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Advanced Computing, Networking and Security, ADCONS 2011
CountryIndia
CitySurathkal
Period16-12-1118-12-11

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Raghavendra, U., Makkithaya, K., & Karunakar, A. K. (2012). Qualitative and quantitative evaluation of correlation based stereo matching algorithms. In Advanced Computing, Networking and Security - International Conference, ADCONS 2011, Revised Selected Papers (Vol. 7135 LNCS, pp. 244-252). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7135 LNCS). https://doi.org/10.1007/978-3-642-29280-4_29