5XSF0 - Sport, Technology and Behaviour

Goal
Become acquainted with the theory and main concepts of digital signal and analysis; make a choice of an approach for a given basic signal/image processing problem; implement the chosen approach in MATLAB and critically evaluate the result; be able to operationalize theoretical concepts from signal/image analysis in a hands-on case study.

Contents
Signal sensing and health/medical imaging is the most important discipline for healthcare diagnosis. Besides this, video cameras play a very important role in the behavior analysis of people in real life and during sports exercises. This course provides in-depth knowledge on signal processing and image processing techniques and the principles of video signal analysis. This course starts with an introduction to 1-D signal sampling and the extension to multi-dimensional signal processing for images and video. Then the course proceeds with the principles and definitions for the frequency-domain representation of 1-D signals and 2-D images and the possibilities for filtering and other processing possibilities in the frequency domain. In a further module, the focus is on the signal and image quality enhancement in various ways. Various noise models are discussed and filtering approaches for reducing the noise. The introduction of color in images for improved understanding is addressed. The second part of the course provides an introduction to image understanding and object/area segmentation to learn 1-D signal and 2-D imaging for health diagnosis. This part starts with simple binary operators and then extends to the detection of points, lines, edges, etc. Secondly, specific region-based segmentation methods are discussed. Features are extracted from images, which is addressed in both the spatial domain directly in the image and a frequency-oriented domain, such as the Gabor transformation. The course concludes with a module on imaging techniques and use cases, where the learned techniques are applied. These cases include computer-aided cancer diagnosis, instrument detection, etc.

Schedule and location: 
8 Weeks of lectures in 2 blocks of 4 hours
Full schedule: 
Date Time Content Module
13 Nov 08.45-10.30 Flux 1.10 Module 1 (Motivation, Image Fundamentals and Signal Transformations), part one
13 Nov 10.45-12.30 Flux 1.10 Computer class (digital images in MATLAB)
16 Nov 13.45-15.30 Flux 1.07 Module 1 (Motivation, Image Fundamentals and Signal Transformations), part two
16 Nov 15.45-17.30 Flux 1.07 Computer class (exercises)
23 Nov 13.45-15.30 Flux 1.07 Module 2 (Basics of Signals, Sampling, Fourier series, Aliasing, and FIR Filtering), part one
23 Nov 15.45-17.30 Flux 1.07 Computer class (spatial filtering of digital images)
27 Nov 08.45-10.30 Flux 1.10 Module 2 (Basics of Signals, Sampling, Fourier series, Aliasing, and FIR Filtering), part two
27 Nov 10.45-12.30 Flux 1.10 Computer class (exercises)
30 Nov 13.45-15.30 Flux 1.07 Module 3 (Discrete Fourier Transform and Filtering), part one
30 Nov 15.45-17.30 Flux 1.07 Computer class (1D signals in spatial and frequency domain)
04 Dec 08.45-10.30 Flux 1.10 Module 3 (Discrete Fourier Transform and Filtering), part two
04 Dec 10.45-12.30 Flux 1.10 Computer class (exercises)
07 Dec 13.45-15.30 Flux 1.07 Module 5 (Features), part one
07 Dec 15.45-17.30 Flux 1.07 Computer class (frequency domain processing)
11 Dec 08.45-10.30 Flux 1.10 Module 5 (Features), part two
11 Dec 10.45-12.30 Flux 1.10 Computer class (exercises)
14 Dec 13.45-15.30 Flux 1.07 Module 4 (Image Restoration and Freq. Filtering & Color Imaging and Transformations), part one
14 Dec 15.45-17.30 Flux 1.07 Computer class (restoration and colors)
18 Dec 08.45-10.30 Flux 1.10 Module 4 (Image Restoration and Freq. Filtering & Color Imaging and Transformations), part two
18 Dec 10.45-12.30 Flux 1.10 Computer class (exercises)
21 Dec 13.45-15.30 Flux 1.07 Module 6 (Segmentation), part one
21 Dec 15.45-17.30 Flux 1.07 Computer class (features)
08 Jan 08.45-10.30 Flux 1.10 Module 6 (Segmentation), part two
08 Jan 10.45-12.30 Flux 1.10 Computer class (exercises)
11 Jan 13.45-15.30 Flux 1.07 Module 7 (Motion analysis & Sports training case study), part one
11 Jan 15.45-17.30 Flux 1.07 computer class (segmentation)
15 Jan 08.45-10.30 Flux 1.10 Module 7 (Motion analysis & Sports training case study), part two
15 Jan 10.45-12.30 Flux 1.10 Computer class (exercises)
18 Jan 13.45-17.30 Flux 1.07 Computer class (motion)
18 Jan 13.45-17.30 Flux 1.07 Computer class (exercises)
19 Jan 08.45-10.30 Room t.b.d. Extra date and time: finish classes
19 Jan 10.45-12.30 Room t.b.d. Recap and questions
Notes: 

Final test (exam): no written exam.
An oral exam organized and subscription by secretariat SPS with Canvas

Slides: 
Instruction sheets: 
Exercises: