A census-based stereo matching algorithm with multiple sparse windows

Kyeong Ryeol Bae, Hyeon Sik Son, Jongkil Hyun, Byungin Moon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Stereo matching is one of the most active research areas in intelligent vehicle technology. In order to apply the stereo matching to intelligent vehicles, it must generate high-accuracy three-dimensional information in real time. For real-time stereo matching, this paper proposes a sparse multi-window method which not only gives robustness to noise but also reduces hardware cost with high matching accuracy. This is achieved by reusing the result of overlapped operations between adjacent windows. The experimental results show that the proposed method can reduce the hardware complexity of stereo matching processors with higher accuracy compared with the conventional window method.

Original languageEnglish
Title of host publicationICUFN 2015 - 7th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages240-245
Number of pages6
ISBN (Electronic)9781479989935
DOIs
StatePublished - 7 Aug 2015
Event7th International Conference on Ubiquitous and Future Networks, ICUFN 2015 - Sapporo, Japan
Duration: 7 Jul 201510 Jul 2015

Publication series

NameInternational Conference on Ubiquitous and Future Networks, ICUFN
Volume2015-August
ISSN (Print)2165-8528
ISSN (Electronic)2165-8536

Conference

Conference7th International Conference on Ubiquitous and Future Networks, ICUFN 2015
Country/TerritoryJapan
CitySapporo
Period7/07/1510/07/15

Keywords

  • census transform
  • Intelligent vehicle
  • sparse multi-window
  • stereo matching

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