Data Segmentation and Model Selection for Computer Vision - A Statistical Approach (Paperback, Softcover reprint of the original 1st ed. 2000)

This edited volume explores several issues relating to parametric segmentation including robust operations, model selection criteria and automatic model selection, plus 2D and 3D scene segmentation. Emphasis is placed on robust model selection with techniques such as robust Mallows Cp, least K-th order statistical model fitting (LKS), and robust regression receiving much attention. With contributions from leading researchers, this is a valuable resource for researchers and graduated students working in computer vision, pattern recognition, image processing and robotics.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	August 2012
First published:	2000
Editors:	Alireza Bab-Hadiashar • David Suter
Dimensions:	235 x 155 x 12mm (L x W x T)
Format:	Paperback
Pages:	208
Edition:	Softcover reprint of the original 1st ed. 2000
ISBN-13:	978-1-4684-9508-9
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition
LSN:	1-4684-9508-9
Barcode:	9781468495089

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