Texturing 3D Models of Real World Objects from Multiple Unregistered Photographic Views

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Date
1999
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Blackwell Publishers Ltd and the Eurographics Association
Abstract
As the efficiency of computer graphic rendering methods is increasing, generating realistic models is now becoming a limiting factor. In this paper we present a new technique to enhance already existing geometry models of real world objects with textures reconstructed from a sparse set of unregistered still photographs. The aim of the proposed technique is the generation of nearly photo-realistic models of arbitrarily shaped objects with minimal effort. In our approach, we require neither a prior calibration of the camera nor a high precision of the user's interaction. Two main problems have to be addressed of which the first is the recovery of the unknown positions and parameters of the camera. An initial estimate of the orientation is calculated from interactively selected point correspondences. Subsequently, the unknown parameters are accurately calculated by minimising a blend of objective functions in a 3D-2D projective registration approach. The key point of the proposed method of registration is a novel filtering approach which utilises the spatial information provided by the geometry model. Second, the individual images have to be combined yielding a set of consistent texture maps. We present a robust method to recover the texture from the photographs thereby preserving high spatial frequencies and eliminating artifacts, particularly specular highlights. Parts of the object not seen in any of the photographs are interpolated in the textured model. Results are shown for three complex example objects with different materials and numerous self-occlusions.
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@article{
10.1111:1467-8659.00345
, journal = {Computer Graphics Forum}, title = {{
Texturing 3D Models of Real World Objects from Multiple Unregistered Photographic Views
}}, author = {
Neugebauer, Peter J.
and
Klein, Konrad
}, year = {
1999
}, publisher = {
Blackwell Publishers Ltd and the Eurographics Association
}, ISSN = {
1467-8659
}, DOI = {
10.1111/1467-8659.00345
} }
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