Affiliation:
1. Louisiana State University, USA
2. Florida International University, USA
Abstract
We review the computation of 3D geometric data mapping, which establishes one-to-one correspondence between or among spatial/spatiotemporal objects. Effective mapping benefits many scientific and engineering tasks that involve the modeling and processing of correlated geometric or image data. We model mapping computation as an optimization problem with certain geometric constraints and go through its general solving pipeline. Different mapping algorithms are discussed and compared according to their formulations of objective functions, constraints, and optimization strategies.
Funder
LEQSF-EPS(2009)-PFUND-133
National Natural Science Foundation of China No. 61170323
LEQSF-EPS(2013)-PFUND-312
National Science Foundation IIS-1320959, IIS-1251095, and CNS-1158701
Louisiana Board of Regents LEQSF(2009-12)-RD-A-06
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
33 articles.
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