A Radiometric Noise Model for Estimating Geometrical Parameters of 3-D Bodies From Multispectral Images

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    Abstract

    Camera images can be used to measure the geometry of man-made objects. An iterative weighted least-squares estimator with knowledge of imaging and reflection models retrieves the geometrical parameters of objects in a 3-D scene from 2-D image projections. We investigate the use of multispectral imagery which allows us to separate diffuse and specular reflection before estimating geometry. We built a multispectral camera measurement system that has been used to capture real images of a cylindrical body. These have been processed to analyse the propagation of radiometric noise from reflection via imaging into reflection component separation. The purpose of this research is the development of a radiometric noise model for use in our geometry estimator.
    Original languageEnglish
    Title of host publicationProceedings of MVA '96
    Subtitle of host publicationIAPR Workshop on Machine Vision Applications : November 12-14 1996, Tokyo, Japan
    Place of PublicationTokyo, Japan
    PublisherKeio University
    Pages414-417
    Number of pages4
    Publication statusPublished - 12 Nov 1996
    EventIAPR Workshop on Machine Vision Applications, MVA 1996 - Tokyo, Japan
    Duration: 12 Nov 199614 Nov 1996

    Workshop

    WorkshopIAPR Workshop on Machine Vision Applications, MVA 1996
    CountryJapan
    CityTokyo
    Period12/11/9614/11/96

    Keywords

    • METIS-113416

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  • Cite this

    Glas, J. C., & van der Heijden, F. (1996). A Radiometric Noise Model for Estimating Geometrical Parameters of 3-D Bodies From Multispectral Images. In Proceedings of MVA '96 : IAPR Workshop on Machine Vision Applications : November 12-14 1996, Tokyo, Japan (pp. 414-417). Tokyo, Japan: Keio University.