The reconstruction of highly detailed, 3D object models is a major goal of current research. Such models can be used in machine vision applications as well as for visualization purposes. The method presented here assumes that there are multiple range and intensity image pairs of an object, all registered to a global coordinate system. The individual range images are then used to create a surface mesh and the associated intensity images are applied to the surface mesh as a texture map. These multiple, textured, range meshes are then used to update a volume grid -- based upon whether a location in the volume grid is known, unknown, or empty -- using information that has the highest confidence for any given voxel. The updated volume grid can then be passed through a marching cubes algorithm with adaptive subdivisions to get a fully textured 3D model. The adaptive marching cubes algorithm takes into account additional information concerning edge weights and texture coordinates to give a smoother surface than that produced with standard marching cubes. Once complete, additional, registered intensity images can be applied to the surface of the object.
[1]
Denis Aluze.
Système de détection et de caractérisation de défauts d'aspect sur des surfaces parfaitement spéculaires et non planes : application au contrôle qualité de produits destinés à l'emballage cosmetique
,
1998
.
[2]
Fabrice Meriaudeau,et al.
Machine vision for the control of reflecting nonplane surfaces
,
1997,
Other Conferences.
[3]
Claudine Coulot.
Etude de l'éclairage de surfaces métalliques pour la vision artificielle : application au contrôle dimensionnel
,
1997
.
[4]
Mongi A. Abidi,et al.
Determining Optimal Sensor Poses in 3-D Object Inspection
,
1998
.
[5]
Juergen Beyerer,et al.
Three-dimensional measurement of specular free-form surfaces with a structured-lighting reflection technique
,
1997,
Other Conferences.
[6]
Frederic Truchetet,et al.
Contrôle temps réel par vision artificielle de tubes métalliques en défilement continu
,
1993
.