Exploration of Shape Variation Using Localized Components Analysis
Year: 2008
Type: article
Abstract: Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania.
Institutions: University of California, Davis, American Museum of Natural History, New York Consortium in Evolutionary Primatology, New York University, University of Oregon, University of California, San Francisco, University of California, Los Angeles, City College of New York, City University of New York
Language: English
Subfield: Geometry and Topology
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2163399942