The module aims to introduce the basic concepts of computer vision, such as image, motion, tracking. It also introduces the basic methods for applications, e.g., image classification, object detection. It finally develops the intuitions and mathematics of the methods in class, and then helps students learn about the difference between theory and practice in experiments.
A Show familiarity with both the theoretical and practical aspects of computer vision;
B Demonstrate knowledge of image formation, measurement, analysis, and motion estimation.
C Implement common methods for robust image matching and recognition, and object detection.
D Apply the practical skills necessary to build computer vision applications.
The teaching philosophy of the module follows very much the philosophy of Syntegrative Education. This has meant that the teaching delivery pattern, which follows more intensive block teaching, allows more meaningful contribution from industry partners. This philosophy is carried through also in terms of assessment, with reduction on the use of exams and increase in coursework, especially problem-based assessments that are project focused. The delivery pattern provides space in the semester for students to concentrate on completing the assessments.
This module will be delivered through a combination of formal lectures and supervised laboratory sessions. There are totally five coursework that will be assigned across the semester.