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Department of Computer Science, Unit Catalogue 2009/10


CM30080: Computer vision

Click here for further information Credits: 6
Click here for further information Level: Honours
Click here for further information Period: Semester 2
Click here for further information Assessment: CW 25%, EX 75%
Click here for further informationSupplementary Assessment: CM30080 Mandatory Extra Work (where allowed by programme regulations)
Click here for further information Requisites: Before taking this unit you must take CM10227, CM10228, CM20220 and CM20219 (and for transitional arrangements CM10134 or CM10140, CM20001 and CM20144) or MA20010, or equivalents)
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 low-level from high-level 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 multi-camera geometry and understand its value in applications such as mosaicing and reconstruction;
4. Understand texture and segmentation, and the role of high-level 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. Multi-camera 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.
NB. Programmes and units are subject to change at any time, in accordance with normal University procedures.