ENGLISH

Shape, Contour and Grouping in Computer Vision

By David A. Forsyth , Roberto Cipolla (auth.) , Vito Di Gesu , Joseph L. Mundy

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
1999
ISBN
3540667229, 9783540667223
DOI
10.1007/3-540-46805-6
LCC
TA1634 .S47 1999
Open Library ID
OL17591621M
Language
english
Format
PDF
Filesize
7 MB (7022422 bytes)
Series
Lecture Notes in Computer Science 1681
Edition
1
Pages
350\339
Topic
Computers
Time added
2011-01-08 23:22:23
Image Processing and Computer Vision; Pattern Reco

Description

Computer vision has been successful in several important applications recently. Vision techniques can now be used to build very good models of buildings from pictures quickly and easily, to overlay operation planning data on a neuros- geon’s view of a patient, and to recognise some of the gestures a user makes to a computer. Object recognition remains a very di cult problem, however. The key questions to understand in recognition seem to be: (1) how objects should be represented and (2) how to manage the line of reasoning that stretches from image data to object identity. An important part of the process of recognition { perhaps, almost all of it { involves assembling bits of image information into helpful groups. There is a wide variety of possible criteria by which these groups could be established { a set of edge points that has a symmetry could be one useful group; others might be a collection of pixels shaded in a particular way, or a set of pixels with coherent colour or texture. Discussing this process of grouping requires a detailed understanding of the relationship between what is seen in the image and what is actually out there in the world.

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