Academic Year:  2017/8 
Owning Department/School:  Department of Computer Science 
Credits:  6 [equivalent to 12 CATS credits] 
Notional Study Hours:  120 
Level:  Honours (FHEQ level 6) 
Period: 
 Semester 2

Assessment Summary:  CW 25%, EX 75% 
Assessment Detail: 
 Course Work (CW 25%)
 Examination (EX 75%)

Supplementary Assessment: 
 Likeforlike reassessment (where allowed by programme regulations)

Requisites: 
Before taking this module you must ( take CM20219 AND take CM20220 ) OR ( take MA10209 AND take MA10210 AND take MA10236 AND take XX10190 )

Description:
 Aims: To understand the ways of analysing images to get information out of them. In order to achieve this it will be necessary to understand the underlyin mathematics and computer techniques.
Learning Outcomes: Students will be able to:
1. Distinguish lowlevel from highlevel Computer Vision methods, and appreciate the vision problem;
2. Describe edge detection as a linear filter and distinguish between linear filtering and morphology;
3. Describe multicamera geometry and understand its value in applications such as mosaicing and reconstruction;
4. Understand texture and segmentation, and the role of highlevel models in recognition;
5. Appreciate a broad range of contemporary Computer Vision.
Skills: Application of number (T/F).
Content: Low level vision: Convolution and linear filtering, edge detection and blurring; the role of scale. Morphology. Texture descriptors.
Multicamera vision: Homographies, epipolar geometry, and the fundamental matrix. Mosaicing and 3D reconstruction.
Segmentation: Hough transforms, unsupervised clustering, scale sieves.
Recognition: The role of prior models: templates, geometry, and statistics.

Programme availability: 
CM30080 is Optional on the following programmes:
Department of Computer Science
 USCMAFB06 : BSc(Hons) Computer Science (Year 3)
 USCMAAB07 : BSc(Hons) Computer Science with Study year abroad (Year 4)
 USCMAKB07 : BSc(Hons) Computer Science with Year long work placement (Year 4)
 USCMAFM01 : MComp(Hons) Computer Science (Year 3)
 USCMAAM02 : MComp(Hons) Computer Science with Study year abroad (Year 4)
 USCMAKM02 : MComp(Hons) Computer Science with Year long work placement (Year 4)
 USCMAFB20 : BSc(Hons) Computer Science and Mathematics (Year 3)
 USCMAAB20 : BSc(Hons) Computer Science and Mathematics with Study year abroad (Year 4)
 USCMAKB20 : BSc(Hons) Computer Science and Mathematics with Year long work placement (Year 4)
 USCMAFM14 : MComp(Hons) Computer Science and Mathematics (Year 3)
 USCMAAM14 : MComp(Hons) Computer Science and Mathematics with Study year abroad (Year 4)
 USCMAKM14 : MComp(Hons) Computer Science and Mathematics with Year long work placement (Year 4)
Department of Mathematical Sciences
 TSMAAFM08 : MSc Modern Applications of Mathematics
 TSMAAWM14 : MSc Modern Applications of Mathematics
 USMAAFB15 : BSc(Hons) Mathematical Sciences (Year 3)
 USMAAAB16 : BSc(Hons) Mathematical Sciences with Study year abroad (Year 4)
 USMAAKB16 : BSc(Hons) Mathematical Sciences with Year long work placement (Year 4)
 USMAAFB13 : BSc(Hons) Mathematics (Year 3)
 USMAAAB14 : BSc(Hons) Mathematics with Study year abroad (Year 4)
 USMAAKB14 : BSc(Hons) Mathematics with Year long work placement (Year 4)
 USMAAFM14 : MMath(Hons) Mathematics (Year 3)
 USMAAFM14 : MMath(Hons) Mathematics (Year 4)
 USMAAAM15 : MMath(Hons) Mathematics with Study year abroad (Year 4)
 USMAAKM15 : MMath(Hons) Mathematics with Year long work placement (Year 4)
 USMAAKM15 : MMath(Hons) Mathematics with Year long work placement (Year 5)
 USMAAFB01 : BSc(Hons) Mathematics and Statistics (Year 3)
 USMAAAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 4)
 USMAAKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 4)
 USMAAFB05 : BSc(Hons) Statistics (Year 3)
 USMAAAB06 : BSc(Hons) Statistics with Study year abroad (Year 4)
 USMAAKB06 : BSc(Hons) Statistics with Year long work placement (Year 4)
