Computer Aided Legal Research on the Internet or Introductory Techniques for 3 D Computer Vision

Computer-Aided Legal Research on the Internet

Author: Craig Simonsen

KEY BENEFIT: This book is an essential tool for paralegal and other legal professionals to bring computer-aided legal research alive. KEY TOPICS: It provides an introduction to computers in the law, reviews and explains sources and evaluation of documents and materials found on the Internet, and features many examples of doing CALR. MARKET: For paralegal and other legal professionals.

Interesting textbook: Microeconomics or The Encyclopaedic Dictionary of Marketing

Introductory Techniques for 3-D Computer Vision

Author: Emanuele Trucco

An applied introduction to modern computer vision, focusing on a set of computational techniques for 3-D imaging, this book covers a wide range of fundamental problems encountered within computer vision and provides detailed algorithmic and theoretical solutions for each. Each chapter concentrates on a specific problem and solves it by building on previous results.

FEATURES:

• Provides a guide to well-tested theory and algorithms including solutions of problems encountered in modern computer vision.
• Contains many practical hints highlighted in the book.
• Develops two parallel tracks in the presentation, showing how fundamental problems are solved using both intensity and range images, the most popular types of images used today.
• Each chapter contains notes on the literature, review questions, numerical exercises, and projects.
• Provides an Internet list for accessing links to test images, demos, archives and additional learning material.

Table of Contents:

	Foreword
	Preface: About this Book
1	Introduction	1
2	Digital Snapshots	15
3	Dealing with Image Noise	51
4	Image Features	67
5	More Image Features	95
6	Camera Calibration	123
7	Stereopsis	139
8	Motion	177
9	Shape from Single-image Cues	219
10	Recognition	247
11	Locating Objects in Space	279
App. A.1	Experiments: Good Practice Hints	307
App. A.2	Numerical Differentiation	311
App. A.3	The Sampling Theorem	314
App. A.4	Projective Geometry	316
App. A.5	Differential Geometry	320
App. A.6	Singular Value Decomposition	322
App. A.7	Robust Estimators and Model Fitting	326
App. A.8	Kalman Filtering	328
App. A.9	Three-dimensional Rotations	332
	Index	335