Fundamentals of Visual Computing
Course Structure:
The course material will be presented through a combination of formal lectures, group readings and discussions, homework-based labs, onsite visits and project work.
3 credits
Learning Objectives:
By the end of the course, you will
- develop a solid understanding of digital processing and analysis of higher dimensional signals
- learn the fundamental of image capture and acquisition
- understand how to represent high dimensional data in spatial and frequency domains
- perform low level image processing such as denoising, enhancement and restoration
- perform high level image analysis such as object localization and modeling
- compare and evaluate state-of-the-art techniques in multi-dimensional data computing
- appreciate the latest research developments in the related area
- develop some experience with real life practical applications
Course Outline:
Fundamentals
- elements of visual perception, image acquisition systems
- image representation, image coding
- image enhancement in the spatial and frequency domains
- color and morphological image processing
- image restoration
Advanced
- feature extraction, object recognition
- shape representation and object modeling including: explicit and implicit models, statistical models, medical representations
- image segmentation including: deformable models, graph based approaches
- image registration
- motion analysis
Applications and Practice
- real life applications e.g. medical imaging, industrial automation, and multi-media processing
- on-site visit
- invited speakers
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