Data Segmentation and Model Selection for Computer Vision

David Suter

ISBN 10: 0387988157 / ISBN 13: 9780387988153

Edité par Springer New York, Springer US Feb 2000, 2000

A propos de cet article

Neuware -The primary focus of this book is on techniques for segmentation of visual data. By 'visual data,' we mean data derived from a single image or from a sequence of images. By 'segmentation' we mean breaking the visual data into meaningful parts or segments. However, in general, we do not mean 'any old data': but data fundamental to the operation of robotic devices such as the range to and motion of objects in a scene. Having said that, much of what is covered in this book is far more general: The above merely describes our driving interests. The central emphasis of this book is that segmentation involves model fitting. We believe this to be true either implicitly (as a conscious or sub conscious guiding principle of those who develop various approaches) or explicitly. What makes model-fitting in computer vision especially hard There are a number of factors involved in answering this question. The amount of data involved is very large. The number of segments and types (models) are not known in advance (and can sometimes rapidly change over time). The sensors we have involve the introduction of noise. Usually, we require fast ('real-time' or near real-time) computation of solutions independent of any human intervention/supervision. Chapter 1 summarizes many of the attempts of computer vision researchers to solve the problem of segmenta tion in these difficult circumstances.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 236 pp. Englisch.

N° de réf. du vendeur 9780387988153

Détails bibliographiques

• Titre: Data Segmentation and Model Selection for Computer Vision
• Éditeur: Springer New York, Springer US Feb 2000
• Date de parution: 2000
• Langue: anglais
• ISBN à 10 chiffres: 0387988157
• ISBN à 13 chiffres: 9780387988153
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

The problem of range and motion segmentation is of major importance in computer vision, image procession, and intelligent robotics. This edited volume explores several issues relating to parametric segmentation emphasizing robust techniques and model selection. With contributions from leading scientists and engineers in the field, this book is a valuable resource for researchers and graduate students working in computer vision, pattern recognition, image processing and robotics.