SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Reflectance and texture of real-world surfaces
ACM Transactions on Graphics (TOG)
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Efficient and realistic visualization of cloth
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
Viewpoint Consistent Texture Synthesis
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Image alignment and stitching: a tutorial
Foundations and Trends® in Computer Graphics and Vision
Bidirectional Texture Function Modeling: A State of the Art Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
A coaxial optical scanner for synchronous acquisition of 3D geometry and surface reflectance
ACM SIGGRAPH 2010 papers
A Multi-camera, Multi-projector Super-Resolution Framework for Structured Light
3DIMPVT '11 Proceedings of the 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission
Rapid synchronous acquisition of geometry and appearance of cultural heritage artefacts
VAST'05 Proceedings of the 6th International conference on Virtual Reality, Archaeology and Intelligent Cultural Heritage
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This paper presents a novel image-based registration method for high-resolution multi-view images of a planar material surface. Contrary to standard registration approaches, this method aligns images based on a true plane of the material's surface and not on a plane defined by registration marks. It combines the camera calibration and the iterative fitting of desired position and slant of the surface plane, image re-registration, and evaluation of the surface alignment. To optimize image compression performance, we use an error of a compression method as a function evaluating the registration quality. The proposed method shows encouraging results on example visualizations of view- and illumination-dependent textures. In addition to a standard multi-view data registration approach, it provides a better alignment of multi-view images and thus allows more detailed visualization using the same compressed parameterization size.