|Course Title||Computer Vision|
|Units of Credit||6|
The course will cover topics from: Introduction, image processing, feature detection and matching, feature-based alignment, image stitching, segmentation, feature tracking, recognition, motion estimation, stereo correspondence and 3-D reconstruction, applications.
The course timetable is available here .
Computer vision develops mathematical techniques for recovering three-dimensional shape and appearance of objects in images (Szeliski, 2010). Vision is difficult because it is an inverse problem, where only insufficient information is available when trying to recover some unknowns. Physics-based and statistical models are used to assist in the task. Current real-world applications are wide-ranging, and include optical character recognition, machine inspection, objection recognition in retail, 3-D model building in photogrammetry, medical imaging, automotive safety, match move in Hollywood (merging computer generated imagery with live action footage), motion capture, surveillance, fingerprint recognition and biometrics and others. This course will provide an introduction to fundamental concepts and an opportunity to develop an application.
After completing this course, students will:
This course contributes to the development of the following graduate capabilities:
|Graduate Capability||Acquired in|
the skills involved in scholarly enquiry
an in-depth engagement with relevant
disciplinary knowledge in its interdisciplinary context
the capacity for analytical and critical
thinking and for creative problem solving
|the ability to engage in independent and reflective learning||
|the skills to locate, evaluate and use relevant information (Information Literacy)||Test, Project|
the capacity for enterprise, initiative and
the skills required for collaborative and
the skills of effective communication
Project Presentation, Demo, Report; Assignment Report
Before commencing this course, students should:
The principal mode of teaching is class lectures. Because of the volume of material available on the subject, lectures are better able to present high level overviews as well as in-depth presentation of selected topics.
The compulsory lab session will provide an opportunity for evaluation and feedback.
|Assessment Type||Marks||Release Date||Due in|
|Assignment||10%||Week 2||Week 4|
|Mid-term test||30%||Week 9|
|Project (multiple stages):||50% (in total):|
|• Stage 1||10%||Week 4||Week 7|
|• Specs of stage 2||10%||Week 7||Week 10|
|• Demo||10%||Week 13|
|• Performance evaluation (during demo and in report)||10%|
|• Report||10%||Fri of Week 13|
|Attendance at labs||10%|
Plagiarism is defined as using the words or ideas of others and presenting them as your own . UNSW and CSE treat plagiarism as academic misconduct, which means that it carries penalties as severe as being excluded from further study at UNSW. There are several on-line sources to help you understand what plagiarism is and how it is dealt with at UNSW:
Make sure that you read and understand these. Ignorance is not accepted as an excuse for plagiarism.
|1||Introduction to Digital Imaging||Arcot Sowmya|
|2||Image Processing||Arcot Sowmya|
|3||Feature Detection and Matching||
|4||Feature-based Alignment and Image Stitching||
|5||Pattern Recognition||Peter Cai|
|7||Feature Tracking||Peter Cai|
|8||Object Recognition||Peter Cai|
|9||Class test||Arcot Sowmya|
|10||Project Stage 2 Specification||
|11||3D Vision||Yang Wang/Arcot Sowmya|
|12||Tracking and Temporal Models||
Yang Wang/Arcot Sowmya
|13||Project Demo||Arcot Sowmya|
Texts and recommended readings:
This course is evaluated each session using the CATEI system.
Based on feedback, the following changes are being made in this offering:
1. An experienced co-lecturer is now available and will co-teach the course.
2. More training for tutors will be provided, to improve the lab experience, feedback on assignments and with programming.
3. The marking criteria will be released before the assessments.
4. To better guide the group project, lab mentors will be assigned to specific groups.
5. Consultation on use of software packages will be encouraged during lab time.
Resource created Thursday 21 July 2016, 10:55:26 AM, last modified Friday 21 July 2017, 04:36:06 PM.