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.
|Title of host publication||Proceedings of MVA '96|
|Subtitle of host publication||IAPR Workshop on Machine Vision Applications : November 12-14 1996, Tokyo, Japan|
|Place of Publication||Tokyo, Japan|
|Number of pages||4|
|Publication status||Published - 12 Nov 1996|
|Event||IAPR Workshop on Machine Vision Applications, MVA 1996 - Tokyo, Japan|
Duration: 12 Nov 1996 → 14 Nov 1996
|Workshop||IAPR Workshop on Machine Vision Applications, MVA 1996|
|Period||12/11/96 → 14/11/96|
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.