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EE5811 - Topics in Computer Vision

Offering Academic Unit
Department of Electrical Engineering
Credit Units
3
Course Duration
One semester
Pre-cursor(s)
Mathematical knowledge reaching the equivalent of [MA3150 Advanced Mathematical Analysis, or MA3151 Advanced Engineering Mathematics] and [MA3160 Probability and Stochastic Processes, or EE3313 Applied Queueing Systems]
and 
Programming knowledge reaching the equivalent of
[CS2363 Computer Programming or equivalent]
Specifically, C programming will be required.
Course Offering Term*:
Semester A 2022/23

* The offering term is subject to change without prior notice
 
Course Aims

This course aims to provide students with an in-depth critical understanding of Computer Vision's principles, concepts, and advanced techniques. The main objective of this course is to develop students with the fundamental knowledge of how machines understand and process data in the visual world. The outline of this course includes the topics of computer vision from the perspectives of low-level image processing (e.g., image mathematical and physical modelling, image enhancement, image coding, and filtering, edge and contour detection, image statistics analysis) and high-level visual semantic understanding (e.g., image recognition, image segmentation, motion analysis), along with different real-world applications where computer vision techniques have been applied. 

Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 50%
Examination: 50%
Examination Duration: 2 hours
 
Detailed Course Information

EE5811.pdf

Useful Links

Department of Electrical Engineering