Affective Computing in Multimedia

Content

This one-semester course provides an introduction to eye tracking in the form of a one part theoretical lecture and one part practical lab session.

Lecture in ZEuS Exercises in ZEuS Lecture in ILIAS

Course Goals

The main objective of the eye tracking course is twofold. First, getting a good understanding of eye tracking theory and methodology. Second, participation in the course will familiarize students with eye tracking hardware and carrying out eye tracking user studies.

Key goals are:

  • Knowledge in working on specific topics in the field of eye tracking.
  • Knowledge of key characteristics of eye movements.
  • Knowledge of the design and implementation cycle of eye tracking user studies.
  • Practical experience in the technical realization of eye tracking user studies.
  • Practical proving of the knowledge in eye tracking user stuies on selected topics.
  • Application of group work skills.
  • Presentation of project work.

Course Content

Current topics in the research focus of the department will be reviewed to gain the necessary basics and will be applied to practical problems. These topics are:

1. Human Visual System

  • The eye and its movements
  • Binocular properties of eye movements
  • Pupil and corneal reflection eye tracking

2. Eye Tracking Systems

  • Types of video-based eye-trackers
  • Properties of eye-trackers

3. Eye Tracking Methodology

  • The need to understand what you are studying
  • Trials and their duration
  • Participant selection
  • Questionnaires and Scales
  • Other Measures

4. Eye Tracking Experiments

  • Building of Experiments
  • Participant Requirements and Ethics
  • Experimental Setup
  • Calibration
  • Preparations for Data Analysis

5. Data Analysis

  • Event Detection
  • Areas of Interest
  • Attention Maps
  • Scanpaths

6. Eye Tracking Applications

    Prerequisites

    None, if taken as a master course. If taken as an advanced course in the bachelor program:

    • basic math courses offered in our bachelor programs
    • algorithms and data structures
    • introduction to computer science including programming

    Knowledge in Matlab is advisable.

    Course Works and Credits

    Credit will be given based on a mid-term and a final presentation of an experimental study in visual quality estimation using physiological sensors. The mid-term presentation should include the the design of the study as well as the proposed evaluation methodology. The final presentation should include the theoretical foundations, the design of the experiment, the data analysis, and the visualization of the results. In addition a written report containing this material must be provided.