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Computer Vision
| Faculteit | Science and Engineering |
| Jaar | 2020/21 |
| Vakcode | WMCS015-05 |
| Vaknaam | Computer Vision |
| Niveau(s) | master |
| Voertaal | Engels |
| Periode | semester II a |
| ECTS | 5 |
| Rooster | rooster.rug.nl |
| Uitgebreide vaknaam | Computer Vision | ||||||||||||||||||||
| Leerdoelen | Presentation of the basic principles of computer vision, in particular multiscale analysis, deformable models, ‘shape from X’ and video analysis, building on the knowledge acquired in Image Processing. Promote understanding of the theoretical (mathematical) backgrounds in modelling higher order vision processes. | ||||||||||||||||||||
| Omschrijving | This course develops the theoretical basis as well as practical algorithms for automatically extracting useful information about the world by carrying out computations on images or image sequences. First, a number of basic image processing concepts are briefly reviewed, such as digitization, preprocessing, image restoration and segmentation. Standard linear image processing algorithms are discussed as well as some concepts and algorithms from nonlinear morphological image processing. Also, some recent results on multiscale image analysis are presented. Then we move to higher level operations, such as object recognition, pattern recognition and three-dimensional scene analysis. Making inferences of a 3D world from 2D pictures requires the analysis of projection methods, geometric transformations and illumination models. We study the shape recovery problem, that is, the question of how object properties such as shape can be reconstructed from features which can be measured in images. As an illustration of the theory we discuss shape from texture, shape from shading, shape from stereo and shape from motion. Practical Information: Lab assignments using an image processing package. As an alternative to the regular practicals, students can elect to do a short research project. | ||||||||||||||||||||
| Uren per week | |||||||||||||||||||||
| Onderwijsvorm | Hoorcollege (LC), Practisch werk (PRC), Werkcollege (T) | ||||||||||||||||||||
| Toetsvorm |
Opdracht (AST), Practisch werk (PR), Schriftelijk tentamen (WE)
(G1=average grade for practicals, G2=grade for written exam,final grade (G1+2*G2)/3 if both Gi>=5, else min((G1+2*G2)/3,5).) |
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| Vaksoort | master | ||||||||||||||||||||
| Coördinator | dr. M.H.F. Wilkinson | ||||||||||||||||||||
| Docent(en) | dr. M.H.F. Wilkinson | ||||||||||||||||||||
| Verplichte literatuur |
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| Entreevoorwaarden | Recommended prior knowledge: Image Processing and/or Signals and Systems | ||||||||||||||||||||
| Opmerkingen | In the academic year 2020-2021, some CS master courses — including Computer Vision — have limited enrollment: - CS students can always enter the course, regardless of whether the course is mandatory for them or not. - Students from other programmes for which this is a *compulsory* course (see list below), can always enter the course. - The number of enrolments for other non-CS students is limited. These students need to meet the course prerequisite requirements as mentioned on Ocasys. Priority is given to students for which the course is an official elective (see list below). - An exception can be made for exchange students, if they have a CS background: please contact the FSE International Office. See here for more info about the enrollment procedure. This course was registered last year with course code INMCV-08 |
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