TY - JOUR
T1 - Automated view and path planning for scalable multi-object 3D scanning
AU - Fan, Xinyi
AU - Zhang, Linguang
AU - Brown, Benedict
AU - Rusinkiewicz, Szymon
N1 - Funding Information:
We would like to thank all the people who have provided helpful suggestions, encouragement, and feedback for this project, particularly Tim Weyrich, Camillo J. Taylor, James Bruce, David Radcliff, Joanna Smith, and the members of the Princeton Graphics Group. We also thank all the reviewers for their constructive comments. This work is supported by NSF grants CCF-1027962, IIS-1012147, and IIS-1421435.
Publisher Copyright:
© 2016 ACM.
PY - 2016/11/11
Y1 - 2016/11/11
N2 - Demand for high-volume 3D scanning of real objects is rapidly growing in a wide range of applications, including online retailing, quality-control for manufacturing, stop motion capture for 3D animation, and archaeological documentation and reconstruction. Although mature technologies exist for high-fidelity 3D model acquisition, deploying them at scale continues to require non-trivial manual labor. We describe a system that allows non-expert users to scan large numbers of physical objects within a reasonable amount of time, and with greater ease. Our system uses novel view- and path-planning algorithms to control a structured-light scanner mounted on a calibrated motorized positioning system. We demonstrate the ability of our prototype to safely, robustly, and automatically acquire 3D models for large collections of small objects.
AB - Demand for high-volume 3D scanning of real objects is rapidly growing in a wide range of applications, including online retailing, quality-control for manufacturing, stop motion capture for 3D animation, and archaeological documentation and reconstruction. Although mature technologies exist for high-fidelity 3D model acquisition, deploying them at scale continues to require non-trivial manual labor. We describe a system that allows non-expert users to scan large numbers of physical objects within a reasonable amount of time, and with greater ease. Our system uses novel view- and path-planning algorithms to control a structured-light scanner mounted on a calibrated motorized positioning system. We demonstrate the ability of our prototype to safely, robustly, and automatically acquire 3D models for large collections of small objects.
KW - 3D acquisition
KW - view planning
UR - http://www.scopus.com/inward/record.url?scp=85112815449&partnerID=8YFLogxK
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U2 - 10.1145/2980179.2980225
DO - 10.1145/2980179.2980225
M3 - Article
AN - SCOPUS:85112815449
SN - 0730-0301
VL - 35
JO - ACM Transactions on Computer Systems
JF - ACM Transactions on Computer Systems
IS - 6
M1 - 2980225
ER -