Dense, time-varying range data acquisition from stereo pairs of thermal and intensity images

Jun Ohya, Fumio Kishino

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

1 Citation (Scopus)

Abstract

We propose a new method for acquiring time-sequential range images that provide dense range data. In our approach, stereo pairs of thermal and intensity images are synchronously acquired and are mutually registered. The thermal images are segmented into isotemperature regions. Contour-based matching is done for the isotemperature regions in the thermal images independently at each time instant, and by temporal correspondence, possible matching pairs of contours are generated. By evaluating the similarities of the pairs, consistent and likely pairs are chosen. To get dense range data, intensity profiles within the isotemperature regions are matched by dynamic programming. Experiments on real scenes, including a sequence showing a moving human being, show promising results.

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherPubl by IEEE
Pages860-865
Number of pages6
ISBN (Print)0818658274
Publication statusPublished - 1994 Jan 1
EventProceedings of the 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Seattle, WA, USA
Duration: 1994 Jun 211994 Jun 23

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Other

OtherProceedings of the 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CitySeattle, WA, USA
Period94/6/2194/6/23

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Ohya, J., & Kishino, F. (1994). Dense, time-varying range data acquisition from stereo pairs of thermal and intensity images. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 860-865). (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). Publ by IEEE.