Disparity estimation from monocular image sequence

Qieshi Zhang, Sei Ichiro Kamata

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

Abstract

This paper proposes a novel method for estimating disparity accurately. To achieve the ideal result, an optimal adjusting framework is proposed to address the noise, occlusions, and outliners. Different from the typical multi-view stereo (MVS) methods, the proposed approach not only use the color constraint, but also use the geometric constraint associating multiple frame from the image sequence. The result shows the disparity with a good visual quality that most of the noise is eliminated, the errors in occlusion area are suppressed and the details of scene objects are preserved.

Original languageEnglish
Title of host publicationSeventh International Conference on Machine Vision, ICMV 2014
EditorsBranislav Vuksanovic, Jianhong Zhou, Antanas Verikas, Petia Radeva
PublisherSPIE
ISBN (Electronic)9781628415605
DOIs
Publication statusPublished - 2015 Jan 1
Event7th International Conference on Machine Vision, ICMV 2014 - Milan, Italy
Duration: 2014 Nov 192014 Nov 21

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9445
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference7th International Conference on Machine Vision, ICMV 2014
CountryItaly
CityMilan
Period14/11/1914/11/21

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Keywords

  • Color constraint
  • Disparity estimation
  • Geometry constraint
  • Multi-view stereo (MVS)

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Zhang, Q., & Kamata, S. I. (2015). Disparity estimation from monocular image sequence. In B. Vuksanovic, J. Zhou, A. Verikas, & P. Radeva (Eds.), Seventh International Conference on Machine Vision, ICMV 2014 [944515] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9445). SPIE. https://doi.org/10.1117/12.2180535