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Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2
A Novel Approach For Texture Shape Recovery
Nice, France
October 13-October 16
ISBN: 0-7695-1950-4
Jing Wang, Rutgers University, NJ
Kristin J. Dana, Rutgers University, NJ
In vision and graphics, there is a sustained interest in capturing accurate 3D shape with various scanning devices. However, the resulting geometric representation is only part of the story. Surface texture of real objects is also an important component of the representation and fine-scale surface geometry such as surface markings, roughness, and imprints, are essential in highly realistic rendering and accurate prediction. We present a novel approach for measuring the fine-scale surface shape of specular surfaces using a curved mirror to view multiple angles in a single image. A distinguishing aspect of our method is that it is designed for specular surfaces, unlike many methods (e.g. laser scanning) which cannot handle highly specular objects. Also, the spatial resolution is very high so that it can resolve very small surface details that are beyond the resolution of standard devices. Furthermore, our approach incorporates the simultaneous use of a bidirectional texture measurement method, so that spatially varying bidirectional reflectance is measured at the same time as surface shape.
Citation:
Jing Wang, Kristin J. Dana, "A Novel Approach For Texture Shape Recovery," iccv, vol. 2, pp.1374, Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2, 2003
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