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2000 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'00) - Volume 1
3-D Model Construction Using Range and Image Data
Hilton Head, South Carolina
June 13-June 15
ISBN: 0-7695-0662-3
This paper deals with the automated creation of geometric and photometric correct 3-D models of the world. Those models can be used for virtual reality, tele-presence, digital cinematography and urban planning applications. The combination of range (dense depth estimates) and image sensing (color information) provides data sets which allow us to create geometrically correct, photorealistic models of high quality. The 3-D models are first built from range data using a volumetric set intersection method previously developed by us. Photometry can be mapped onto these models by registering features from both the 3-D and 2-D data sets. Range data segmentation algorithms have been developed to identify planar regions, determine linear features from planar intersections that can serve as features for registration with 2-D imagery lines, and reduce the overall complexity of the models. Results are shown for building models of large buildings on our campus using real data acquired from multiple sensors.
Citation:
Ioannis Stamos, Peter K. Allen, "3-D Model Construction Using Range and Image Data," cvpr, vol. 1, pp.1531, 2000 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'00) - Volume 1, 2000
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