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Cursus: 201100254
201100254
Advanced Computer Vision and Pattern Recognition
Cursus informatie
Cursus201100254
Studiepunten (ECTS)5
CursustypeCursus
VoertaalEngels
Contactpersoondr.ir. L.J. Spreeuwers
E-maill.j.spreeuwers@utwente.nl
Docenten
Contactpersoon van de cursus
dr.ir. L.J. Spreeuwers
Docent
dr.ir. L.J. Spreeuwers
Docent
prof.dr.ir. R.N.J. Veldhuis
Collegejaar2014
Aanvangsblok
2B
AanmeldingsprocedureZelf aanmelden via OSIRIS Student
Inschrijven via OSIRISJa
Leerdoelen
-
Inhoud
This course is a follow-up of the ‘image processing and computer vision’
course, and as such a very good preparation for students who want to do their masters assignment in biometrics (Master specialisation Computer Vision and Biometrics), medical imaging or robotics.  The course addresses advanced methods for image segmentation, object tracking and motion analysis in images, 3D computer vision and 3D reconstruction from e.g. stereo images and statistical pattern recognition for image analysis, e.g. face recognition.

Main Goals
  1. Students have knowledge of advanced computer vision and pattern recognition techniques and are able to apply them.
  2. Students can read and understand scientific papers on advanced computer vision and pattern recognition and are able to implement (part of) the methods described to verify results reported in the papers.
Contents
The course consists of four main subjects:
  1. Basics of statistical pattern recognition: Classification, Detection, Learning, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Parameter estimation.
  2. Advanced image segmentation techniques: Mean shift, Snakes, Level-set, Active Shape Model (ASM), Watershed
  3. Motion analysis: Tracking in 3D, Kalman filter, Optic flow
  4. 3D computer vision and 3D image analysis: Fundamentals, Stereo, 3D vision
Form of the course
The course is project based, meaning the students actively acquire knowledge of the above mentioned subjects by applying them and investigating their performance. The course consists of a number of lectures where students present the acquired and applied knowledge followed by discussion with their fellow students and the teachers. The projects are carried out in groups of 2-4 students (individual projects are also possible). The students can choose the subjects for the projects from a predefined list that changes every year. Examples of projects in previous years are: lip reading from video, people tracking across multiple cameras and 3D reconstruction using 2D video, face recognition from video. For each project a number of basic methods must be studied and their application investigated. During the final part of the course, the aim is to realize a working system resulting in a demonstration and a report in the form of a publication.
 

Examination
    1. The students have to prepare for the lectures and present the basic methods they studied and their application to the projects.
    2. The students have to write a report of max 10 pages in the form of a scientific paper
    3. At the end of the course there will be closing event where all students are present and each of them presents the results in a short presentation and if possible, a demonstration.
    4. To get a grade, a student must fulfill the first 3 conditions.

The final mark is based on the report.
Voorkennis
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DEELNEMENDE OPLEIDING
M-EE
Verplicht materiaal
-
Aanbevolen materiaal
Boek
Image processing, Analysis and Machine Vision, 3rd edition Milan Sonka, Vaclav Hlavac, Roger Boyle; ISBN: 0495244384
Werkvormen
Project

Toetsen
Assignment

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