CSE190-C00

Topics in CSE:

BIOMETRICS

 

Winter 2010

Section Id: 683441

Tuesday, Thursday, 2:00pm – 3:20pm

HSS 2305A 

http://www.cs.ucsd.edu/classes/wi10/cse190/

 

 

 

Instructor: David Kriegman

Office: EBU3b, Room 4120

Phone: (858) 822-2424

Email: kriegman at cs.ucsd.edu

Office Hour: Wednesday 1:30-2:30

 

Class Description: Biometrics is the science of determining a person's identity by measuring his/her physiological characteristics. Fingerprinting, most widely known for its role in forensics, was used to sign and validate contracts in the 7th century during China's Tang Dynasty; today, laptop computers use automatic fingerprint recognition instead of passwords. Technologies are being developed to verify or identify individuals based on measurements of the face, hand geometry, iris, retina, finger, ear, voice, speech, signature, lip motion, skin reflectance, DNA, and even body odor. In this course we will explore the advances in biometrics as well as the machine learning techniques behind them.

 

Required Text: none

See E-reserve at: http://reserves.ucsd.edu/eres/coursepage.aspx?cid=15505&page=docs

 

Prerequisites: Linear algebra and Multivariable calculus (e.g. Math 20A & 20F), probability and statistics (e.g., Math 183 or CSE190, A Practical Introduction to Probability and Statistics), a good working knowledge of C, C++ or Matlab programming.

 

Programming: Assignments will include both written problem sets and programming assignments in Matlab. Students can either purchase the Matlab student edition or use copies available on University machines such as are available in the APE Lab

 

Grading:

Assignments: 40%

Quiz: 10%

Final Project: 50%

 

Late Policy: Written homework will be due in class and accepted thereafter with a penalty of 10% per day starting from the due date. Programming assignments will have a hand-in procedure described with the assignment, and also has a 10% per day late penalty. No assignments will be accepted after the graded assignments have been returned or the solutions have been released.

 

Assignments:

Homework 0: Getting Started with Matlab, Due Thursday, Jan. 14, 2010). Follow the assignment from CSE152 as described in the following PDF file with Assignment 0.  A test image for the assignment is here. You only need to hand it the hardcopy, not the electronic part.

Homework 1: Bayesian Classifiers , Due January 26, 2010

Project: Description of the project

Homework 2: More Classification, Due February 11, 2010

Homework 3: Hand geometry-based recognition, due March 2, 2010. Data files: part1, part 2 (jpgs, pdfs)

Homework 4: Finding the Candy Man using fingerprints, March 12, 210, Data files.

 

 

Syllabus

 

[ Note that this Syllabus is tentative & subject to change]

Week

Date/Link

To lecture

notes

Topic/Readings

1

Jan. 5

 

 

Biometric Recognition, A.K. Jain, Nature, September 2007 

Linear algebra review

Random variables review

 

Jan. 7

Statistical Pattern Recognition, Bayesian Decision Theory

Duda & Hart, Chapter 1, 2.1-2.4

2

Jan. 12

Bayesian Decision Theory, Gaussian distributions

Duda & Hart, Sec. 2.5-2.8

 

Jan. 14

Image Formation

3

Jan. 19

Parameter Estimation,

Duda & Hart, Sec. 3.1-3.5, 3.7

 

Jan. 21

Parameter Estimation, cont

4

Jan. 26

Non-parametric classification

Duda & Hart, Sec. 4.1-4.5

 

Jan. 28

Nearest Neighbor density estimation and classification

5

Feb. 2

Linear Discriminant Functions

 

Feb. 4

More notes

Support Vector Machines

1. Duda, Hart & Stork, Sec. 5.11

2. "A Tutorial on Support Vector Machines for Pattern Recognition," Christopher J.C. Burges

6

Feb. 9

Face Recognition I

 

Feb. 11

Face Recognition II

7

Feb. 16

Face Recognition III

 

Feb. 18

Face Recognition IV -- Illumination

8

Feb. 23

Hand Geometry and Recognition

R. Zunkel: Hand Geometry based Verification, BIOMETRICS: Personal Identification in Networked Society, Springer, 1998

 

Feb. 25

Fingerprint Recognition I

Minutiae extraction

9

Mar. 2

Fingerprint Recognition II: Minutae Matching

See Section 6.1.4 of  Computer Vision: Algorithms and Applications, Rick Szeliski, Draft

 

Mar. 4

Iris Recognition

J. Daugman: Recognizing Persons by Their Iris Patterns, BIOMETRICS: Personal Identification in Networked Society, Springer, 1998.

J. Daugman (1993) "High confidence visual recognition of persons by a test of statistical independence." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15(11), pp. 1148-1161

10

Mar. 11

Biometrics Policy

 

Mar. 12

Project presentations

 

 

Notes and links

 

Programming languages: 

The primary language will be Matlab. . Click here for Serge Belongiee’s Matlab resource links.

 

Computer Vision Books

1.     Introductory Techniques for 3-D Computer Vision, Trucco and Verri (textbook for CSE152)

2.     “Computer Vision: Algorithms and Applications”, Richard Szeliski, A draft of the book, which is currently being written, is available at: http://research.microsoft.com/en-us/um/people/szeliski/Book/.

 

 

General Biometrics Books

1. D. Maltoni, D. Maio, A. K. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition, Springer Verlag, 2003.

2. K. Jain, R. Bolle, S. Pankanti (Eds.), BIOMETRICS: Personal Identification in Networked Society, Kluwer Academic Publishers, 1999.

3. Ruud M. Bolle et al., Guide to Biometrics, Springer, 2004.

 

 

Some useful links: