9.913 | Fall 2004 | Graduate

Pattern Recognition for Machine Vision

Lecture Notes

LEC # TOPICS NOTES
1 Overview, Introduction

Course Introduction (PDF - 2.6 MB)

Vision: Feature Extraction Overview (PDF - 1.9 MB)

Quick MATLAB® Tutorial (PDF)

2 Vision - Image Formation and Processing  
3 Vision - Feature Extraction I (PDF - 2.4 MB)
4 PR/Vis - Feature Extraction II/Bayesian Decisions

Part 1: Bayesian Decision Theory (PDF - 1.1 MB)

Part 2: Principal and Independent Component Analysis (PDF)

5 PR - Density Estimation (PDF - 1.4 MB)
6 PR - Classification (PDF)
7 Biological Object Recognition  
8 PR - Clustering

Part 1: Techniques for Clustering (PDF)

Part 2: An Application of Clustering (PDF)

9 Paper Discussion  
10 App I - Object Detection/Recognition (PDF - 1.3 MB)
11 App II - Morphable Models  
12

App III - Tracking

Guest Lecturer: Christopher R. Wren

(PDF - 1.0 MB) Courtesy of Christopher R. Wren. Used with permission.
13 App IV - Gesture and Action Recognition (PDF - 3.0 MB)
14 Project Presentation  

Course Info

As Taught In
Fall 2004
Level
Learning Resource Types
Simulation Videos
Lecture Notes
Presentation Assignments
Activity Assignments