Overview

An in-depth introduction to the core concepts of post-desktop user interface engineering. Current topics in UI research, in particular non-desktop based interaction, mobile device interaction, augmented and mixed reality, and advanced sensor and output technologies.


Announcements

31.05.2016
Exercise 2 grades are now online (see Exercises section).
26.04.2016
Case Study and Exercise 1 grades are now online (see Exercises and Case Study sections).
16.03.2016
Exercise 1 new dataset released. Link to download in slides (direct link)
16.03.2016
Exercise 1 due date extended of 1 week. New deadline on 23.03.2016
09.03.2016
Annotated slides for week 3 online. Added some clarifications on mRmR
12.02.2016
The course starts on Wednesday 24.02.16.

Learning Objectives

Students will learn about fundamental aspects pertaining to the design and implementation of modern (non-desktop) user interfaces. Students will understand the basics of human cognition and capabilities as well as gain an overview of technologies for input and output of data. The core competency acquired through this course is a solid foundation in data-driven algorithms to process and interpret human input into computing systems.

At the end of the course students should be able to understand and apply advanced hardware and software technologies to sense and interpret user input. Students will be able to develop systems that incorporate non-standard sensor and display technologies and will be able to apply data-driven algorithms in order to extract semantic meaning from raw sensor data.


Schedule

Wk.Date ContentSlides
1 24.02.
Introduction

Introduction to class contents, HCI research field & admin

slides slides (annotated)
2 02.03.
ML for HCI Pt. I

Classification / regression, SVMs

slides slides (annotated)
3 09.03.
ML for HCI Pt. II

Non-linear SVM & Decision Trees

slides slides (annotated)
4 16.03.
ML for HCI Pt. III

Ensemble Methods

slides slides (annotated) pptx (wth videos)
5 23.03.
Case Study: Programm Committee
6 30.03.
No Class (Easter)
7 06.04.
Dynamic gestures

HMMs / DL

slides slides (annotated)
8 13.04.
Motion Analysis

Filtering & Optical Flow

slides slides (annotated)
9 20.04.
User Modelling

Basics of Perception

slides slides(annotated)
10 27.04.
Motor system & text input

Fitts' law, language & touch models

slides slides(annotated)
11 04.05.
Computational UI Design

Algorithmic design of user interfaces

slides slides (annotated)
12 11.05.
No Class (ACM SIGCHI)
13 18.05.
Virtual Reality

Most important concepts in VR.

slides pptx (with videos, large file size)
14 25.05.
Augmented Reality

Most important concepts in AR.

slides pptx (with videos, large file size)
15 01.06.
Research Topics & Review
No slides

Exercises

There will be 4 exercises (3 programming assignments and 1 case study). The exercises will constitute 40 % of the final grade. Assignments have to be completed individually. It is ok to discuss with your team members but you have to write your own code.

Exercise sheets and solutions will only be accessible from within the ETH network.

Exercise Assignment Solution Due date
Exercise 1 Homework 1 Slides Additional Slides Final Grades 23.03.2016
Exercise 2 Homework 2 Slides Final Grades 13.04.2016
Exercise 3 Homework 3 Matlab Template Python Template Slides Final Grades 01.06.2016

Case Study

We will do one in class case study, simulating a program committee meeting. This is a mandatory and graded part of the course requirements. The paper review form can be found here. The final grades for this exercise can be found here.


Exam

The performance assessment is an oral exam conducted at the end of the semester. It will constitute 60% of the final grade.