Computer Science – Performance
Scientific paper
Jan 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21543803l&link_type=abstract
American Astronomical Society, AAS Meeting #215, #438.03; Bulletin of the American Astronomical Society, Vol. 42, p.392
Computer Science
Performance
Scientific paper
We are developing software to automate the detection and classification of moving objects in astronomical data sets based on the Random Sample Consensus (RANSAC) algorithm for model fitting. In data sets designed to simulate the expected performance of the Widefield Infrared Survey Explorer (WISE) we achieved an identification reliability of 100 % and completeness of 94.6±1.3 % for moving sources observed in 6 of 14 frames, with better completeness for higher repeat sources. We have also achieved our performance goal of being able to handle the quantity of data from WISE in real time using a current but modest personal computer.
We would like to thank NASA for funding the WISE project.
Lake Sean E.
Wright Louis E.
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