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Data segmentation and model selection for computer vision : a statistical approach

Author: Alireza Bab-Hadiashar; David Suter, (Computer scientist)
Publisher: New York : Springer, ©2000.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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 including robust operations, model selection criteria and automatic model selection, and 2D and 3D scene segmentation. Emphasis is placed on robust model selection with techniques such as robust Mallows Cp,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Data segmentation and model selection for computer vision.
New York : Springer, ©2000
(DLC) 99036220
(OCoLC)41580625
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Alireza Bab-Hadiashar; David Suter, (Computer scientist)
ISBN: 9780387215280 038721528X 9781468495089 1468495089 6610189862 9786610189861
OCLC Number: 666928936
Description: 1 online resource (xviii, 208 pages) : illustrations (some color)
Contents: 2D and 3D scene segmentation for robotic vision / R.A. Jarvis --
Robust regression methods and model selection / E. Ronchetti --
Robust measures of evidence for variable selection / S. Sommer, R.G. Staudte --
Model selection criteria for geometric inference / K. Kanatani --
Range and motion segmentation / A. Bab-Hadiashar, D. Suter --
Model selection for structure and motion recovery from multiple images / P.H.S. Torr.
Responsibility: Alireza Bab-Hadiashar, David Suter, editors.

Abstract:

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.  Read more...

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