Data Segmentation and Model Selection for Computer Vision

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.

Inhalt
I Historical Review.- 1 2D and 3D Scene Segmentation for Robotic Vision.- II Statistical and Geometrical Foundations.- 2 Robust Regression Methods and Model Selection.- 3 Robust Measures of Evidence for Variable Selection.- 4 Model Selection Criteria for Geometric Inference.- III Segmentation and Model Selection: Range and Motion.- 5 Range and Motion Segmentation.- 6 Model Selection for Structure and Motion Recovery from Multiple Images.- References.