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CM50249: Visual understanding 2

Follow this link for further information on academic years Academic Year: 2017/8
Further information on owning departmentsOwning Department/School: Department of Computer Science
Further information on credits Credits: 12      [equivalent to 24 CATS credits]
Further information on notional study hours Notional Study Hours: 240
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: CW 100%
Further information on unit assessment Assessment Detail:
  • CW1 (CW 100%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites: Before or while taking this module you must take CM50248
Undergraduate students selecting this unit should note the teaching structure
Further information on descriptions Description: Aims:
To understand and critically evaluate the fundamental and advanced aspects of computer vision and be equipped with the skills needed to specify and undertake an independent project.

Learning Outcomes:
Upon Completion of this unit students will be able to:
1. Describe state-of-art techniques in mid-level and high-level computer vision.
2. Understand the relationship between the segmentation, classification and identification of images and video.
3. Explain the importance of Machine Leaning to Computer Vision.
4. Demonstrate the practical application of theory to experiment.

Skills:
Linear Algebra (TFA), Probability (TFA), Programming (TFA), Experimentation (TFA)

Content:
Segmentation by clustering: GMMs, mean-shift, graph-cuts, and Berkeley's segmentation algorithm.
Object Recognition: bag-of words, model fitting with AAMs, and DPMs.
Experimental assessment methods: PR curves, confusion matrices.
Applications of Computer Vision.
Further information on programme availabilityProgramme availability:

CM50249 is Optional on the following programmes:

Department of Computer Science
  • RSCM-AFD05 : Doctor of Engineering (EngD) Digital Entertainment
  • TSCM-AFM37 : MSc Digital Entertainment
  • TSCM-AWM37 : MSc Digital Entertainment
  • USCM-AFM01 : MComp(Hons) Computer Science (Year 4)
  • USCM-AAM02 : MComp(Hons) Computer Science with Study year abroad (Year 5)
  • USCM-AKM02 : MComp(Hons) Computer Science with Year long work placement (Year 5)
  • USCM-AFM14 : MComp(Hons) Computer Science and Mathematics (Year 4)
  • USCM-AAM14 : MComp(Hons) Computer Science and Mathematics with Study year abroad (Year 5)
  • USCM-AKM14 : MComp(Hons) Computer Science and Mathematics with Year long work placement (Year 5)

Notes: