Dynamic sensing and modeling (supported by AFOSR)
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The ability to obtain a digital geometric model directly from
physical objects marks a revolutionary step in the information era.
Three-dimensional (3D) digitization is a process to create
three-dimensional computer models of a physical object. Such reconstructed
3D shape models have become indispensable in a variety of applications such
as product design and manufacturing in aerospace, automotive, and die and
mold industry, patient-specific medical device design and analysis, as well
as target recognition and scene understanding in homeland security and
military applications
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The objective of this research is to develop foundational
shape digitization theories and algorithms for a multimodal digitization
system that can couple 3D sensing and post-sensing shape reconstruction in
a dynamic manner in order to fundamentally improve digitization automation
level, speed, efficiency and the resulting surface quality. (video)
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Multi-stage
multi-sensor digitization system (Minolta Vivid 9i area sensor, Optimet
line/point sensor, touch probe)
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Acquired
point cloud data from the system
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Low-discrepancy
based dynamic sensing-and-modeling
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Representative
publications:
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Huang, Y., Qian, X. and Chen, S., "Multi-Sensor Calibration
through Iterative Registration and Fusion," Computer-Aided Design,
Vol. 41, No. 4, pp. 240-255, April 2009.
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Huang, Y. and Qian, X., "An efficient sensing
localization algorithm for free-form surface digitization," ASME
Transactions Journal of Computing and Information Science in Engineering,
Vol. 8, No. 2, June 2008. [pdf]
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Huang, Y. and Qian, X., "Dynamic B-spline Surface
Reconstruction: Closing the Sensing-and-Modeling Loop in 3D
Digitization," Computer-Aided Design, Vol. 39, No. 11, pp.
987-1002, Nov 2007. [pdf]
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Huang, Y. and Qian, X., "A dynamic sensing-and-modeling
approach to 3D point- and area-sensor integration," ASME Transactions Journal
of Manufacturing Science and Engineering, Vol. 129, pp. 623- 635, June
2007. [pdf]
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