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Introduction

Computer Vision is a field of study that generally attempts to duplicate the abilities of human vision through acquiring, processing, analysing, and understanding digital images captured with a camera. This unit will focus on computer vision in a context of advanced human computer interaction, specifically how computer vision can make possible many interesting advanced interfaces. For example, computer vision can make a computer understand the body/hand gestures of users. Computer vision can also determine the position and orientation of user's viewpoint, in case of Augmented Reality (AR) applications, to display and stabilise (co-locate) digital contents in the real world as if they do exist. The unit will cover in both theory and practical implementations of several computer vision techniques such as image segmentation, object recognition, feature extraction (e.g. SIFT), structured light pattern (e.g. Kinect), Structure-from-Motion (SfM), projective geometry (e.g. Mono SLAM, PTAM). Tutorial sessions will aim to introduce different tools in MATLAB to help take the theoretical knowledges of computer vision into developing an interface application.

Summary 2020

Unit name Computer Vision in Interactive Systems
Unit code KIT412
Credit points 12.5
Faculty/School College of Sciences and Engineering
School of Technology, Environments and Design
Discipline Information & Communication Technology
Coordinator

Winyu Chinthammit

Level Honours
Available as student elective? Yes
Breadth Unit? No

Availability

Note

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About Census Dates

Fees

Requisites

Prerequisites

  • Enrolled in an honours degree or DN/HD in two level 400/500/600/700 units or equivalent of intermediate level programming skills

Teaching

Teaching Pattern

3hrs lectures,1hr tutorial weekly

Assessment

40% exam, 60% in-semester (Assignment 1 (10%); Assignment 2 (10%); Assignment 3 (20%); Assignment 4 (20%))

TimetableView the lecture timetable | View the full unit timetable

Textbooks

RequiredNone

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