July 2004
Intermediate to advanced
688 pages
19h 3m
English
Content preview from Emerging Topics in Computer VisionBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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4.2. Models and Estimation Problems
In this section, we examine the basic concepts involved in parameter estimation. We describe the different components of a model and show how to find the adequate model for a given computer vision problem. Estimation is analyzed as a generic problem, and the differences between nonrobust and robust methods are emphasized. We also discuss the role of the optimization criterion in solving an estimation problem.
4.2.1. Elements of a model
The goal of data analysis is to provide, for data spanning a very high-dimensional space, an equivalent low-dimensional representation. A set of measurements consisting of n data vectors yi ∊ Rq can be regarded as a point in Rnq. If the data can be described by a model with only ...
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