Computer Vision 2023-24
School Of Computer Science And Electronic Engineering
Module - Semester 1
Indicative content includes:
- Image formation, image representation, fundamentals of human luminance and color vision, segmentation, re-sampling. Solving problems using a modern library such as OpenCV,
- Point operations, convolution, linear filters, morphological operators, image histograms, and histogram equalization, 2D image transformations, image pyramids.
- Edge detectors, Hough transform, segmentation, feature detectors, feature descriptors, feature matching.
- Digital camera, display devices. colour calibration, gamma correction, limitations of human visual perception.
- More advanced computer vision topics, e.g. person tracking, trajectory, surveillance, security, controlling processes (e.g., robots), navigation, comp-human interaction (e.g., gestures), automatic inspection. Ethical considerations incl. data collection/management, informed consent, privacy, surveillance.
- Apply image processing filters and operators to achieve given goals of an imaging system.
- Construct software to process image data, both in a general sense and for Computer Vision.
- Effectively use image representations to solve computer vision problems
- Give examples of computer vision applications, associate them with CV algorithms.
- Make informed decisions on the selection of imaging and display technologies for a task at hand.
- Use computer vision techniques to implement feature detection and tracking.