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Data segmentation and model selection for computer vision: a statistical approach
List of Titles
Data segmentation and model selection for computer vision: a statistical approach
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/219754
- Title
- Data segmentation and model selection for computer vision: a statistical approach
- Author(s)
- Bab-Hadiashar, Alireza; Suter, David
- 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. 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.
- Publication type
- Book
- Publication year
- 2000
- Keyword(s)
- 2D & 3D scene analysis; Automatic model selection; Model selection criteria; Parametric segmentation; Robust model selection; Robust operations
- Publisher
- Springer
- ISBN
- 9780387988153, 0387988157
- Publisher URL
- http://www.springer.com/computer/image+processing/book/978-0-387-98815-3
- Copyright
- Copyright © 2000 Springer-Verlag New York, Inc.
- Peer reviewed
