Biometrics, Fall 2024

Aug 21, 2024

Details

Course: COMP 388-002 / COMP 488-002 Computer Science Topics
Level: Undergraduate and Graduate
Instructor: Daniel Moreira (dmoreira1@luc.edu)
TA: Fiona Nicdao (fnicdao@luc.edu)

Lectures: MON and WED, 4:15 to 5:30 PM, in person at 408 Mundelein Center
Office Hours: MON and WED evenings, and FRI afternoons,
310 Doyle Center or Zoom, by appointment
Sakai: https://sakai.luc.edu/x/9WVTcd

Overview

How do computers match a person’s fingerprints? Do they still use the same techniques proposed in the XIX century? How do computers identify people captured in a video? Do they leverage the depicted faces only, or can they use other traits such as gait or voice? How about iris recognition as portrayed in the movies? Is it really possible? What happens in the case of people who look very similar, such as identical twins? Which traits are more reliable and robust to impersonation or prone to falsification? These are some of the questions we will address in this course, whose main topic is Biometrics. In a nutshell, Biometrics is the study of techniques to identify individuals through their physical, chemical, and behavioral traits, such as fingerprints, face, iris, DNA, voice, gait, etc. Our focus will be on the technical and ethical aspects of computer-aided Biometrics, discussing the issues of going from simple and benign authentication to the more problematic case of surveillance. The course will have an intense hands-on approach, with the collection of samples and implementation of fingerprint, face, and iris recognition.

Requirements to attend this course are basic programming skills (especially Python). This course and its materials are also available in Sakai.

Schedule

Important Dates

  • 08/26 - First Class.
  • 09/02 - Labor Day, no classes.
  • 09/09 - 1st Coding Class.
  • 09/25 - 2nd Coding Class and 1st Assignment Deadline.
  • 10/07 - Fall Break, no classes.
  • 10/09 - Midterm Exam.
  • 10/23 - 3rd Coding Class.
  • 10/24 - 2nd Assignment Deadline.
  • 11/06 - 4th Coding Class.
  • 11/12 - 3rd Assignment Deadline.
  • 11/18 - Dr. Czajka’s Talk.
  • 11/20 - Dr. Bačić’s Talk.
  • 11/27 - Thanksgiving, no classes.
  • 12/04 - Project presentations.
  • 12/08 - 4th Assignment deadline
  • 12/09 - Final Exam.

Notebooks (for coding classes)

Invited Talks
Dr. Adam Czajka
 Dr. Adam Czajka
Associate Professor
Department of Computer Science and Engineering
University of Notre Dame
Do you want a better presentation attack detection algorithm? Tell it where to look!

This lecture will discuss Dr. Czajka’s group’s research efforts on establishing a holistic framework for human-machine supervision cycle to enable (a) human-guided design of computer vision methods to make the biometric presentation attack detection mechanisms generalize better to unknown attack instruments, and (b) creation of computer-aided methods of assisting human examiners in detecting of fake inputs. The lecture will use iris recognition and iris presentation attack detection as use cases for the discussed methodologies.
Dr. Dinko Bačić
 Dr. Dinko Bačić
Assistant Professor
Quinlan School of Business
Loyola University Chicago
Exploring biometric data in research and teaching: Insights from the UX & BIOMETRICS LAB

The integration of biometric data into research and teaching has unlocked exciting opportunities to understand human behavior and decision-making. This talk will provide an overview of cutting-edge research and innovative teaching methods developed at the UX & Biometrics Lab (uxbiometriclab.com). The presentation will introduce how biometric data — captured through technologies like eye tracking, galvanic skin response, and facial muscle movement — enables researchers to uncover subconscious responses and enhance the study of user experiences. Examples of ongoing research projects will demonstrate the potential of biometric insights to understand user engagement, inform system design, improve decision-making frameworks, and optimize information visualization. Additionally, the talk will highlight how biometric research is incorporated into experiential learning for students, fostering critical thinking and technical skills.

Grading

Concept  Interval (%)  Concept  Interval (%)  Concept  Interval (%)  Concept  Interval (%)
A [96, 100) B+ [88, 92) C+ [76, 80) D+ [64, 68)
A- [92, 96) B [84, 88) C [72, 76) D [60, 64)
B- [80, 84) C- [68, 72) F (0, 60)

Distribution

Undergraduate (COMP 388-002)   Graduate (COMP 488-002)
Assignments (4)   40% 25%
Exams (2) 50% 40%
Project +10% (optional and extra) 25%
Participation 10% 10%
On the News +1% (extra) +1% (extra)

Assignments

Late Policy
Deduction of 10% of the maximum possible grade for each day of delay.

Exams

Project

  • Written report and presentation, work alone or in groups.

Possible Topics

  • Implementation of complete class attendance system.
  • Presentation attack (performance, detection, and mitigation) of fingerprint recognition.
  • Presentation attack of face recognition.
  • Presentation attack of iris recognition.
  • Implementation of recognition of traits other than fingerprints, face, and iris.
  • Presentation and implementation of state-of-the-art scientific publications.
  • Discussion about the ethical aspects of Biometrics and surveillance.

Participation

  • Class Attendance: every presence counts.
  • Today-I-missed Statements: every submission counts.
  • Grace Cards: use them to pardon class absence or late work.
  • Religious holidays will be honored according to the student’s faith, as stated in https://tinyurl.com/4uujcuw2.

Today-I-missed Statements

After every attended class, each student will have to submit (through Sakai) a short paragraph answering one of the following:

  1. What is your biggest question after class? OR
  2. What was the most interesting point you learned today?

Inspired by Dr. Sandra Avila.

Today I missed…

Grace Cards

Each student has three Grace Cards, which will allow them to avoid losing points because of class absence. They might also use their cards to excuse late-delivered assignments and give a one-week extension. The cards are not valid to dismiss or postpone exam and final project dates. Students may use their cards at their own discretion, as long as they clearly communicate the instructor.

Life happens, be wise.

Biometrics on the News

Posted by the students and the instructor on Sakai.

  1. Ethical Problems continue to plague biometric studies of Chinese minority groups.
  2. Illegible Fingerprints.
  3. Koalas have fingerprints almost identical to ours.
  4. The mystery of the Phantom of Heilbronn.
  5. Major breach found in biometrics system.
  6. On Airports’ Horizon: Facial Recognition.
  7. Scrutiny of Iris-scanning Crypto Project Grows.
  8. Unusual Biometric Techniques.
  9. Scammers used AI to replicate son’s voice.

References

  • Jain, Ross, and Nandakumar. Introduction to Biometrics. Springer Books, 2011.
  • Jain, Flynn, and Ross. Handbook of Biometrics. Springer Books, 2008.

Learning Outcomes

At the end of the course, students will master the theoretical foundations, key techniques, and applications of Biometrics to real-world scenarios. Their repertoire will include:

  • Understanding the fundamentals of Biometrics.
  • Developing and implementing Biometric algorithms.
  • Assessing the performance of Biometric systems.
  • Applying Biometrics to real-world applications.
  • Identifying the privacy and ethics issues of Biometric systems.
  • Being up-to-date with emerging trends in Biometrics.

Graduate students (within COMP 488-002), in particular, will acquire the following extra skills:

  • Reading, peer-reviewing, and writing scientific papers about Biometrics.
  • Conducting research in Biometrics, from the design of hypotheses, development of solutions, and comparison to existing baselines, to the design and execution of experiments.

Academic Integrity

Students are expected to adhere to the LUC statements on academic integrity available at https://tinyurl.com/5n6ru62s. These policies fully apply to this course. The penalty for task-wise academic misconduct is losing all the task’s points. Multiple events of misconduct will incur in failing the entire course (with an F grade). All cases of academic misconduct will be reported to the proper department offices. Lastly, students are not allowed to use AI assisted technology (such as ChatGPT) along the entirety of the course, unless explicitly authorized by the instructor.

Accommodations

Students who have disabilities and wish to request academic accommodations are advised to contact the Student Accessibility Center (SAC) at 773-508-3700 or sac@luc.edu as soon as possible. SAC will provide accommodation letters that, once shared with the instructor, will be fully honored as per the terms of their content with no further questions and total confidentiality.

Teaching Biometrics Fingerprint Recognition Iris Recognition Face Recognition
Daniel Moreira
Daniel Moreira
Assistant Professor of Computer Science

Computer scientist with interests in (but not limited to) Computer Vision, Machine Learning, Media Forensics, and Biometrics.