Title:
Statistical optimization for geometric computation : theory and practice
Personal Author:
Series:
Machine intelligence and pattern recognition v18
Publication Information:
New York : Elsevier, 1996
ISBN:
9780444824271
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000003631839 | TJ211 K37 1996 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
This work discusses mathematical foundations of statistical inference for building a 3D-model for the environment from image and sensor data that contain noise. Examples of synthetic and real data are given to demonstrate the benefits of optimal methods over conventional ones.
Table of Contents
| 1 Introduction |
| 2 Fundamentals of Linear Algebra |
| 3 Probabilities and Statistical Estimation |
| 4 Representation of Geometric Objects |
| 5 Geometric Correction |
| 6 3-D Computation by Stereo Vision |
| 7 Parametric Fitting |
| 8 Optimal Filter |
| 9 Renormalization |
| 10 Applications of Geometric Estimation |
| 11 3-D Motion Analysis |
| 12 3-D Interpretation of Optical Flow |
| 13 Information Criterion for Model Selection |
| 14 General Theory of Geometric Estimation |
| References |
| Index |
