Local Features in Natural Images via Singularity Theory (Paperback, 1st ed. 2016)

This monograph considers a basic problem in the computer analysis of natural images, which are images of scenes involving multiple objects that are obtained by a camera lens or a viewer's eye. The goal is to detect geometric features of objects in the image and to separate regions of the objects with distinct visual properties. When the scene is illuminated by a single principal light source, we further include the visual clues resulting from the interaction of the geometric features of objects, the shade/shadow regions on the objects, and the "apparent contours". We do so by a mathematical analysis using a repertoire of methods in singularity theory. This is applied for generic light directions of both the "stable configurations" for these interactions, whose features remain unchanged under small viewer movement, and the generic changes which occur under changes of view directions. These may then be used to differentiate between objects and determine their shapes and positions.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Lecture Notes in Mathematics, 2165
Release date:	October 2016
First published:	2016
Authors:	James Damon • Peter Giblin • Gareth Haslinger
Dimensions:	235 x 155 x 14mm (L x W x T)
Format:	Paperback
Pages:	255
Edition:	1st ed. 2016
ISBN-13:	978-3-319-41470-6
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Promotions
LSN:	3-319-41470-4
Barcode:	9783319414706

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