Note: This is an archived Handbook entry from 2008.Search for this in the current handbook
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2008:Semester 2, - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 24 hours of lectures, 11 hours of workshops; Non-contact time commitment: 84 hours |
Total Time Commitment: Not available
|Prerequisites:||Previous study in artificial intelligence (433-303 or equivalent) and computer graphics (433-380 or equivalent) would be helpful but is not essential.|
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorDr. Les Kitchen
|Subject Overview:|| |
This subject gives an introduction to computer vision and image processing. Computer vision is the business of using computers to extract useful information automatically from digital images and videos; image processing is the business of transforming images to be more suitable for human interpretation, storage, transmission, or subsequent analysis by computer vision. Computer vision and image processing can be used in such practical applications as: automated inspection for quality control in industry; medical imaging; visual guidance for robots; face recognition; automated surveillance and monitoring; remote sensing - to a degree providing a visual sense for machines.
Topics to be covered include low-level, mid-level, and high-level vision; image formation; synopsis of human vision; segmentation and feature extraction; perceptual organisation; visual motion analysis; stereo; shape from shading and other properties; colour processing; shape analysis; texture; the Hough transform; image compression; object recognition; image interpretation and scene understanding.
|Assessment:||A two-hour written exam (50%), a programming project expected to take approx. 24 hours (20%) and a report of 10-12 pages in length about some topic in computer vision and giving an in-class presentation about it of around 15 minutes duration (30%).|
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
|Generic Skills:||On successful completion, students will: |
|Notes:||Credit may not be gained for both 433-483: Computer Vision and Image Processing and 433-683: Computer Vision and Image Processing.|
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