Superordinate Shape Classification Using Natural Shape Statistics

Autor/inn/en	Wilder, John; Feldman, Jacob; Singh, Manish
Titel	Superordinate Shape Classification Using Natural Shape Statistics
Quelle	In: Cognition, 119 (2011) 3, S.325-340 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0010-0277
DOI	10.1016/j.cognition.2011.01.009
Schlagwörter	Classification; Statistics; Experiments; Bayesian Statistics; Human Body; Evaluation Methods; Investigations; Surveys; Databases + Suchen Sie Ihr Suchwort? Classification system; Klassifikation; Klassifikationssystem; Statistik; Erprobung; Menschlicher Körper; Untersuchung; Survey; Umfrage; Befragung; Datenbank
Abstract	This paper investigates the classification of shapes into broad natural categories such as "animal" or "leaf". We asked whether such coarse classifications can be achieved by a simple statistical classification of the shape skeleton. We surveyed databases of natural shapes, extracting shape skeletons and tabulating their parameters within each class, seeking shape statistics that effectively discriminated the classes. We conducted two experiments in which human subjects were asked to classify novel shapes into the same natural classes. We compared subjects' classifications to those of a naive Bayesian classifier based on the natural shape statistics, and found good agreement. We conclude that human superordinate shape classifications can be well understood as involving a simple statistical classification of the shape skeleton that has been "tuned" to the natural statistics of shape. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10