ITO5221 Intelligent image and video analysis
Faculty of Information Technology
ITO5221 Intelligent image and video analysis is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2027. It needs ITO5047, ITO5201 or ITO5197.
- Credit points
- 6
- Offered in 2027
- Other periods
- Monash Online
- Assessment
- No exam
- 3 tasks
Reviews
No reviews yetNo reviews yet. Be the first to review ITO5221.
Requisites
Before ITO5221
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
After ITO5221
No unit lists ITO5221 as a prerequisite in the 2027 handbook.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit will discuss the fundamental and modern concepts in image and video analysis. You will be introduced to the basics of image processing and low-level vision. The topics related to image formation, operations, features and segmentation will enable you with the understanding for developing vision enabled systems. Concepts related to convolutional neural networks (CNN) will be introduced and recent examples will be thoroughly analysed. Recent computer vision concepts will be discussed from a deep learning perspective. The unit will be balanced between the theoretical and the practical implementation aspects of computer vision.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| Teaching period 1 | Monash Online | Mo |
| Teaching period 5 | Monash Online | Mo |
Assessment
- Collage and cross correlationProject30%
- Neural networks for image classificationProject30%
- Coding problemProject40%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
describe image analysis and low-level vision.
- 2
describe semantic image and video understanding techniques.
- 3
describe CNN and their applications.
- 4
implement and extend existing computer vision algorithms.
- 5
evaluate and compare techniques suitable for adding vision capability to unimodal and multimodal intelligent systems.
Workload and teaching
- Teaching approachOnline learning
A minimum of 144 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.
Contacts
- Chief Examiners
- Dr Toan Do