Data segmentation and model selection for computer vision : a statistical approach /
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...
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
[2000]
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| 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, least K-th order statistical model fitting (LKS), and robust regression receiving much attention. With contributions from leading researchers, this book is a valuable resource for researchers and graduate students working in computer vision, pattern recognition, image processing, and robotics. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xviii, 208 pages) : illustrations (some color) |
| Bibliography: | Includes bibliographical references (pages [185]-204). |
| ISBN: | 9780387215280 (electronic bk.) 038721528X (electronic bk.) |