Studying online

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CITS4402 Computer Vision

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 1UWA (Perth)Face to face
Semester 1OnlineOnline timetabled
Content
Computer vision is the science of automatically computing information and making decisions from an observed image, image set or an image sequence. It combines concepts from 'image processing' (in the spatial and frequency domains) and 'pattern recognition'. Computer vision has a wide number of potential applications, including satellite imaging, control and measurement, industrial inspection, surveillance (e.g. face recognition) and medical applications. This unit covers topics such as binary image analysis, greyscale image manipulation, linear and nonlinear filtering, feature extraction, image enhancement, image segmentation and recognition. It also covers camera calibration and projective geometry and how three-dimensional information can be reconstructed from single images, stereo pairs of images and motion sequences. In the future, it is anticipated that computer vision systems will become prevailing, and that vision technology will be more applied across a broad range of business and consumer products. This will result in a strong industry demand for computer vision engineers—for people who understand vision technology and know how to apply it in real-world problems.
Outcomes
Students are able to (1) explain computer vision problems in writing; (2) write MATLAB code to solve computer vision problems; (3) describe the theories and principles in computer vision; (4) conduct independent research on a chosen research topic, write a small research report, and give an oral presentation; (5) demonstrate logical thinking and problem-solving skills; (6) process images in both the spatial and frequency domains; (7) explain the technical theory behind formation of images; and (8) critique various methodologies for solving problems in computer vision and image processing.
Assessment
Indicative assessments in this unit are as follows: (1) laboratory solutions (5% per lab); (2) research project; and (3) final exam. Further information is available in the unit outline.

Supplementary assessment is not available in this unit.
Unit Coordinator(s)
Professor Mohammed Bennamoun
Unit rules
Prerequisites:
enrolment in the
MJD-ARTIF Artificial Intelligence or
HON-CMSSE Computer Science and Software Engineering or
62530 Master of Data Science or
62550 Master of Professional Engineering (Biomedical Engineering or Electrical and Electronic Engineering or Software Engineering)
Co-requisites:
Nil.
Advisable prior study:
CITS2401 Computer Analysis and Visualisation and MATH1012 Mathematical Theory and Methods (ID 6013) (Note: Students must have the ability to program in a high-level programming language and the ability to reason in linear algebra and calculus.)
Incompatibility:
CITS4240 Computer Vision
  • The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
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  • Unit readings, including any essential textbooks, are listed in the unit outline for each unit, one week prior the commencement of study. The unit outline will be available via the LMS and the UWA Handbook one week prior the commencement of study. Reading lists and essential textbooks are subject to change each semester. Information on essential textbooks will also be made available on the Essential Textbooks. This website is updated regularly in the lead up to semester so content may change. It is recommended that students purchase essential textbooks for convenience due to the frequency with which they will be required during the unit. A limited number of textbooks will be made available from the Library in print and will also be made available online wherever possible. Essential textbooks can be purchased from the commercial vendors to secure the best deal. The Student Guild can provide assistance on where to purchase books if required. Books can be purchased second hand at the Guild Secondhand bookshop (second floor, Guild Village), which is located on campus.