Current Subjects in Computer Science Lectures to be given at the University of Applied Sciences Stralsund  (Germany) Department of Electrical Engineering and Computer Science

September 2006

Evaluation  Objectives  Course description  Bibliografy Seminar schedule Lecture slides Practice exercises 

Useful links on Pattern Recognition

Lecturers: Arturo Gil, Luis Payá. Former Lecturers: César Fernández,   Asun Vicente

Contact email: c.fernandez@umh.es   arturo.gil@umh.es   suni@umh.es   lpaya@umh.es

Departament: INGENIERÍA DE SISTEMAS INDUSTRIALES

Universidad Miguel Hernández.   Elche, Spain

Evaluation:

The total qualification will be obtained as follows:

- Practice reports: 50% of the total mark.

- Final test (multiple choice test): 50% of the total mark.

 

Objectives:

- To understand the interrelation between Computer Vision, Pattern Recognition and Machine Learning.

- To review the main computer vision techniques both in theory and in practice.

- To learn some pattern recognition fundamentals.

- To build in practice a face recognition system.

- To analyse the different machine learning techniques, showing their advantages and drawbacks.

 

 Course description (pdf)

Bibliografy:

- "Pattern classification". R.O. Duda, P.E. Hart, D.G. Stork. Wiley, 2000.

- "Machine learning".T.M. Mitchell. McGraw-Hill, 1997.

- "Data mining". I.H. Witten, E. Frank. Morgan Kaufmann, 2000.

 

 

Seminar Schedule (September 2006):

	Monday 11th	Tuesday 12th	Wednesday 13th	Thursday 14th	Friday 15th					Monday 18th
8:00-9:30					Lecture
9:45-11:15			Lecture	Lecture	Lecture					Test
11:30-13:00			Lecture	Lecture	Practice
14:00-15:30					Practice
15:45-17:15			Practice	Practice	Practice

 

 Lecture notes (slides):

Course Introduction

 

Seminar #1:  Computer vision

 

Introduction

Capturing images

Image features, Image Transformations

Edge extraction

Segmentation

Introduction to 3D vision

 

 

Seminar #2:  Pattern recognition

Introduction to Pattern Recognition

Bayesian decision theory

Feature Extraction and Selection Methods

Face recognition

Robot navigation

 

    Additional Information:

        more info. about PCA: PCA (appendix from David Guillamet's PhD thesis)

        more info. about ICA: http://www.cis.hut.fi/aapo/papers/NCS99web/

        more info. about Face Recognition: http://www.face-rec.org/general-info/

        Paper : Eigenfaces for Recognition, Turk, M. & Pentland, A. , Journal of Cognitive
Neuroscience, 3, 71-86, 1991.
        Paper : Statistical Pattern Recognition: A Review, Anil K. Jain,  Robert P. W. Duin an Jianchang Mao, IEEE Transactions on Pattern Analysis and Machine Intelligence,22, 1, pp.4-37, 2000.

 

 

 Practice exercises (and data):

 

SEMINAR	PRACTICE TITLE	EXERCISES	DATA
Computer vision	00-Introduction to Matlab   01-Image Processing Toolbox   02-Segmentation	PDF(309KB)     PDF(819KB)      PDF(819KB)	images.zip
Pattern recognition	P1:Face recognition system based on PCA	PDF(3091KB)	p1.zip
	P2: Adquisition of real images of faces	PDF(3945KB)	trim_face.m
	P3:Testing our faces	PDF(146KB)	faces1_5.zip faces6_9.zip faces10_13.zip