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86138 |
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|a Johnson, Micah K.
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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|a Johnson, Micah K.
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|a Cole, Forrester
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|a Raj, Alvin
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|a Adelson, Edward H.
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|a Cole, Forrester
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|a Raj, Alvin
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|a Adelson, Edward H.
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|a Microgeometry capture using an elastomeric sensor
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|b Association for Computing Machinery (ACM),
|c 2014-04-14T12:48:54Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/86138
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|a We describe a system for capturing microscopic surface geometry. The system extends the retrographic sensor [Johnson and Adelson 2009] to the microscopic domain, demonstrating spatial resolution as small as 2 microns. In contrast to existing microgeometry capture techniques, the system is not affected by the optical characteristics of the surface being measured---it captures the same geometry whether the object is matte, glossy, or transparent. In addition, the hardware design allows for a variety of form factors, including a hand-held device that can be used to capture high-resolution surface geometry in the field. We achieve these results with a combination of improved sensor materials, illumination design, and reconstruction algorithm, as compared to the original sensor of Johnson and Adelson [2009].
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|a National Science Foundation (U.S.) (Grant 0739255)
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|a National Institutes of Health (U.S.) (Contract 1-R01-EY019292-01)
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|a en_US
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|a Article
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|t ACM SIGGRAPH 2011 papers (SIGGRAPH '11)
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