Biometrics: CS
4737 and CS 6737
Classroom: 627 MUDD
Times:
T TH 1:10 pm – 2:25 pm
Web page : http://www1.cs.columbia.edu/~belhumeur/courses/biometrics/2013/biometrics.html
Prof.
Peter N. Belhumeur
http://www.cs.columbia.edu/~belhumeur/
Email: belhumeur@cs.columbia.edu
Office: 623 CEPSR
Phone: 212-939-7087
Office
Hours: Mon 8:30-10:00am
TAs
Jiongxin Liu
Email: liujx09@cs.columbia.edu
Office: CEPSR 6LW4
Office
Hours: Wed 5:00-7:00pm
Thomas Berg Office:
CEPSR 6LW4
Office
Hours: Mon 4:00-6:00pm
Yi-Yin Chang Office:
CEPSR 6LW4
Office
Hours: Tue 5:00-6:00pm
Kun Rong Office:
CEPSR 6LW4
Office
Hours: Wed 4:00-5:00pm
The
earliest known use of biometrics dates back to the 7th century during China's
Tang Dynasty; during this period fingerprints were used to sign and validate
contracts. Over the last century, biometrics -- the science for determining a
person's identity by measuring his/her physiological characteristics -- has
grown enormously. 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 latest advances in
biometrics as well as the machine learning techniques behind them. Students
will learn how these technologies work and how they are sometimes defeated.
Grading will be based on homework assignments and a final project. There will
be no midterm or final exam. Prerequisites: a background at the sophomore level
in computer science, engineering, or like discipline.
Questions? Please check the F.A.Q. Assignments Turn in your assignments by dropping them in the mailbox marked Assignments marked as
"(last year)" have not yet been updated for this year's class. Do not do them yet. They will change. Assignment 1
due October 1
Assignment 2
due October 8
PDF
of
Book Questions
Assignment 3 (last year) Trainfile Testfile
Assignment 4 (last year) Trainfile Testfile
Handpoints
Assignment 5 (last year)
Trainfile Testfile
Assignment 6 (last year) Faces
Folds
matlab code:
vlfeat_and_libsvm
read_lfw_folds
roc
Email: tberg@cs.columbia.edu
Email: yc2828@columbia.edu
Email: kr2496@columbia.eduOverview
Text
Pattern Classification, Duda,
Hart, and Stork
Sections Covered:
Chapter 1, 2.1—2.7, 3.1—3.8
Matlab, Student Version
F.A.Q.
Lectures
Introduction
to Biometrics
Introduction
to Face Recogntion
Basic
Probability + Introduction to Pattern Classification
Bayes Decision Theory
Notes
on Matrix Differentiation
Whitening
Transform Code
PCA
and Eigenfaces
LDA
and Fisherfaces
Decision
Trees
Support
Vector Machines
Hand Written Notes on
Pattern Classification
Nonparametric
Techniques
Plant
Identification
DNA
Barcoding
Physics
of Image Formation
Face
Detection and Face Recognition
Face
Recognition and Face Search
Iris
Recognition Daugman Paper Industry Sales Pitch
Fingerprints
Face
Detection
Topics
Biometrics
in the TA room on the first floor of Mudd (map).
Final Project Project
Description +
Project
Presentations +
Final Project Report
Additional
Datasets: PIE WITH 2
POSES
COMPLETE
UNPROCESSED PIE
Resources
Datasets
BCFD aligned
and cropped (compressed version)
BCFD aligned
and cropped (high-resolution 16 bit)
