Microgeometry capture using an elastomeric sensor

• Main Authors: Johnson, Micah K. (Contributor), Cole, Forrester (Contributor), Raj, Alvin (Contributor), Adelson, Edward H. (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor)
• Format: Article
• Language: English
• Published: Association for Computing Machinery (ACM), 2014-04-14T12:48:54Z.
• Subjects: Article
• Online Access: Get fulltext

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].
National Science Foundation (U.S.) (Grant 0739255)
National Institutes of Health (U.S.) (Contract 1-R01-EY019292-01)