Image-to-Geometry Registration: a Mutual Information Method exploiting Illumination-related Geometric Properties

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Date
2009
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Publisher
The Eurographics Association and Blackwell Publishing Ltd
Abstract
This work concerns a novel study in the field of image-to-geometry registration. Our approach takes inspiration from medical imaging, in particular from multi-modal image registration. Most of the algorithms developed in this domain, where the images to register come from different sensors (CT, X-ray, PET), are based on Mutual Information, a statistical measure of non-linear correlation between two data sources. The main idea is to use mutual information as a similarity measure between the image to be registered and renderings of the model geometry, in order to drive the registration in an iterative optimization framework. We demonstrate that some illumination-related geometric properties, such as surface normals, ambient occlusion and reflection directions can be used for this purpose. After a comprehensive analysis of such properties we propose a way to combine these sources of information in order to improve the performance of our automatic registration algorithm. The proposed approach can robustly cover a wide range of real cases and can be easily extended.
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@article{
10.1111:j.1467-8659.2009.01552.x
, journal = {Computer Graphics Forum}, title = {{
Image-to-Geometry Registration: a Mutual Information Method exploiting Illumination-related Geometric Properties
}}, author = {
Corsini, Massimiliano
and
Dellepiane, Matteo
and
Ponchio, Federico
and
Scopigno, Roberto
}, year = {
2009
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd
}, ISSN = {
1467-8659
}, DOI = {
10.1111/j.1467-8659.2009.01552.x
} }
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