CE/CZ 4001 Virtual and Augmented Reality


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CE/CZ 4001 – Virtual and Augmented Reality

Course Code Course Title Pre‐requisites Pre‐requisite for No of AUs
Contact Hours

CE/CZ 4001 Virtual and Augmented Reality CZ 2003: Computer Graphics and Visualization NIL 3

Lectures 24 TEL 0

Tutorials 12

Student

3

presentations

Course Aims
Virtual and augmented reality is becoming a powerful technology for engineers to design and implement applications ranging from manufacturing and medical to media and entertainment. Virtual reality refers to techniques that build imaginary worlds in computers. Augmented reality adds cues by overlaying computer‐generated images onto the real world. An understanding of the hardware, software and algorithms for virtual and augmented reality allows engineers like you to push the limits of the technology and develop useful applications.
The prerequisite of this course is CZ2003 Computer Graphics and Visualization, which covers fundamentals of 3D modelling and animation.
Intended Learning Outcomes (ILO)
Each lecture module contains the motivation, fundamentals and mathematical background, hardware, software and algorithms in virtual and augmented reality. Practical problems with their solutions will be studied in tutorials. You will gain hands‐on experiences through the laboratory assignments. Upon the successful completion of this course, you shall be able to:
1. Explain what is virtual and augmented reality and how it can simulate and interact with the real‐ world;
2. Identify typical problems associated with virtual and augmented reality; 3. Describe some examples of real‐world applications; 4. Design and implement a working system using available tools based on the concepts and
mathematics learnt in this course

Course Content

Topics

Lectures (Hours)

1 Virtual Reality Platform

Project Window; Scene View; Hierarchy Window;

2

Inspector Window; Game View

2 Graphics

Primitive Shapes, Transforming Shapes; Controlling

2

Appearance with Materials; Lighting, Camera; Shader,

Texture; Particle System

3 Physics

Rigidbody; Colliders; Joints; Character Controllers;

2

Physics Debug Visualization

4 Animation

Workflow and Setup of Animations: Objects,

2

Characters, Properties; Animation Clips; Humanoid

Animation Retargeting

5 Navigation Inner Workings; Building NavMesh: Surface Modifier,

Volume, Link; NavMesh Agent; NavMesh Obstacle;

2

Creating Off-mesh Link; Building Hight Mesh,

Navigation Area and Cost

6 Particle System

Unified representation for rigid objects, deformable

2

objects, liquid, gas, and cloth; Dynamics

7 eLearning 2 Project Development

8 Introduction to Augmented Reality Definition and challenges; introduction to augmented 2 reality engine; case study of a specific engine, e.g. ARToolKit.

9 Displays for Augmented Reality

History; augmented reality display technologies; head-

2

mounted displays; hand-held displays; spatial displays;

perceptual issues.

10 Tracking, Recognition and Registration Tracking techniques: sensor-based, video-based,

hybrid; recognition: feature detection and

2

matching; calibration and registration: projection

methods.

11 Rendering and Augmentation

Geometric model and transformations; rendering

2

framework; augmentation; interaction.

12 Examples of Augmented Reality System

Example systems to link augmented reality concepts to

2

real-world applications; challenges.

Tutorials (Hours)
1 1 1 1
1 1 1 1
1
1
1 1

Presentations (Hours) 0 0 0 0
0 0 0 0
0
0
0 0

13 Project Presentation Check for Hours

0

0

3

24

12

3

Assessment (includes both continuous and summative assessment) a) Final Examination: 60% b) Project written report: 20% c) Project oral presentation: 20%

CE/CZ 4003 – Computer Vision

Course

CE/CZ 4003

Code

Course

Computer Vision

Title

Pre‐

NIL

requisites

Pre‐

NIL

requisite

for

No of AUs 3

Contact Hours

Lectures

26 TEL 0

Tutorials 13

Laboratories ‐

Course Aims
This course aims to introduce you basic concepts and technologies of computer vision, and develop skills to implement widely used algorithms to process real vision tasks. This course presents you with digital image acquisition, representation, processing, recognition, and 3D reconstruction, to gain understanding of algorithm/system design, analytical tools, and practical implementations of various computer vision applications. You will be equipped with fundamental knowledge, practical skills and the insights for future development in this area.
Intended Learning Outcomes (ILO)
Upon the successful completion of this course, you shall be able to:
1. Describe the fundamental computer vision concepts; 2. Explain the advantages and disadvantages of the common computer vision techniques; 3. Implement the basic computer vision algorithms; 4. Apply computer vision techniques to solve simple real problems.

Course Content Topics
1 Introduction to computer vision Background and applications;
2 Principles of Camera Systems Imaging systems, basic thin‐lens optics, digitization, image representation;
3 Image Enhancement in the Spatial domain Histogram operations, linear and nonlinear filtering;
4 Image Enhancement in the Frequency domain Fourier transform, low‐pass, high‐pass and band‐pass filters;
5 Colour Basics of colour; Edge Processing
6 Edge representations, edge filtering, Canny edge detection, Hough transform;
7 Region Processing Region representations, thresholding, texture‐based segmentation; Imaging Geometry
8 3D Coordinate Systems, camera perspective projection, camera parameters and calibration; 3D Stereo Vision
9 Parallax and 2D triangulation, appearance‐based matching and feature‐ based matching, 3D reconstruction; Object Recognition
10 Supervised and unsupervised learning, bag‐of‐words model for general object recognition; Check for Hours

Lectures (Hours)
1 2 3 3 2 3 3 3
3
3 =26

Tutorials (Hours)
1 2 2 1 1 2 1
1
2 =13

Assessment (includes both continuous and summative assessment)
a) Final examination: 60% b) Project 1: 20% c) Project 2: 20%

CE/CZ 4013 – Distributed Systems

Course Code Course Title Pre‐ requisites Pre‐ requisite for No of AUs Contact Hours

CE/CZ 4013
Distributed Systems
CE/CZ 2005: Operating System CE 3005: Computer Networks OR CZ 3006: Net‐Centric Computing NIL

3 Lectures

26 TEL 0

Tutorials 13

Course Aims
This course aims to develop your understanding of the basic architectures, algorithms and design principles of distributed computing systems, and how they meet the demands of contemporary distributed applications.
This course provides an introductory but broad perspective of distributed systems, and is relevant for anyone pursuing a career in the IT/ICT industry – including those in product design and development, network/system administration, as well as, given the proliferation of IT in all walks of our lives, in executive roles across industries and government.
Intended Learning Outcomes (ILO)
This course introduces distributed systems at an elementary level. Upon the successful completion of this course, you shall be able to:
1. Explain the fundamental concepts and main features of distributed systems. 2. Describe the architectures of distributed systems. 3. Describe the functions of software components and common services to support
distributed applications. 4. Analyse and apply the basic distributed algorithms. 5. Apply key design principles to an implementation of distributed system.

Course Content

Topics

Lectures (Hours)

Tutorials (Hours)

1 Characteristics of distributed systems and system

models

Fundamental characteristics of distributed systems, 3

1

resource sharing, issues and problems in distributed

systems, architecture models, fundamental models.

2 Interprocess communication

Transport services, external data representation, 2

1

marshalling and unmarshalling, request-reply protocol

over UDP, request-reply protocol over TCP.

3 Distributed objects and remote invocation

Distributed object model, architecture of remote 2

2

method invocation, Java RMI.

4 Distributed file systems

Distributed file system requirements, Sun network 3

1

file system, Andrew file system, Coda file system.

5 Peer-to-peer systems

Introduction to P2P systems and applications, 3

1

unstructured P2P file sharing, structured DHT

systems.

6 Name services Names, name services, Domain Name System.

2

1

7 Time and global states

Clock synchronization algorithms, logical time, 4

2

logical clocks, vector clocks, global states,

distributed debugging.

8 Coordination and agreement

Distributed mutual exclusion algorithms, election 3

2

algorithms, consensus problems.

9 Replication and consistency

Benefits of replication, requirements of replication, 4

2

consistency models, consistency protocols.

Check for Hours

=26

=13

Assessment
a) Final Examination: 60% b) Course Project: 40%

CE/CZ 4015 – Simulation and Modelling

Course Code Course Title Pre‐ requisites
Pre‐ requisite for No of AUs Contact Hours

CE/CZ 4015
Simulation and Modelling
CE/CZ 1007: Data Structures CE/CZ 1011: Engineering Maths I NIL

3 Lectures

26 TEL 0

Tutorials 13

Laboratories 8

Course Aims
Modelling and Simulation (M&S) course aims to equip you with one of the most important techniques to study real‐time complex systems. M&S is an essential tool in many areas of science and engineering and has many applications, ranging from system analysis, decision support, to virtual environments. Thus, this course will introduce some fundamental techniques in M&S and build an understanding of the systems and tools of this field.
This course provides an introduction to system simulation and modelling techniques for complex dynamic systems. While the focus of this course is on how to analyze complex systems using computer simulation, some basic mathematical techniques will also be discussed. Various modelling, simulation and performance analysis techniques of complex systems will be discussed in this course with the emphasis on discrete event systems.
Intended Learning Outcomes (ILO) Upon the successful completion of this course, you shall be able to:
1. Determine the properties of different types of physical systems and different types of simulations that are suitable to analyze their behaviors;
2. Analyze data collected from real world and build input models for simulation studies; 3. Conduct various simulation studies to investigate the behaviors of complex systems; 4. Conduct statistical analysis of the simulation outputs; and 5. Analyze discrete event systems through the competent use of computer simulation methods
and mathematical modeling techniques.

Course Content

S/ Topics N 1 Introduction

Lecture Hours Tutorial Hours

Nature of simulation, The concept of systems,

models and simulation, Steps in a good

simulation study,

1

1

2 Different Types of Simulation

Monte Carlo simulation, Continuous system

simulation, Discrete event simulation,

Simulation clock, Time advance mechanisms

3

1

3 Simulation World View and Simulation

Software

Event-scheduling world view, Process-

interaction world view, General purpose

programming language vs. simulation software

3

1

4 Basic Probability and Statistical Models for

Simulation

Random variable, PDF, Mean, Variance,

Correlation, The Law of large numbers, Central

Limit Theorem, Sampling, Confidence interval,

Statistical tests.

2

1

5 Random Numbers and Random Variate

Generation

Middle-square method, LCG, Inverse

Transform, Convolution, Composition,

Acceptance-rejection,

3

2

6 Input Modelling

Data collection, Identifying the distribution with

data, MLE, Goodness-of-fit tests (Chi-Square

Test, Kolmogorov-Smirnov test), Arrival

process

3

2

7 Verification and Validation of Simulation

Models

Basic concepts, Verification techniques,

Calibration and validation of models

2

1

8 Output Analysis

2

1

Output analysis for terminating simulations, Output analysis for steady-state simulations, Variance Reduction Technique - Antithetic variates 9 Comparison of Alternative Designs

Pair-t approach, Multiple comparison problem,

Variance Reduction Technique - Common

random numbers

2

1

10 Queueing Models

Basic properties, Performance measures,

Kendall notation, Little’s Law, Analysis of

M/M/1 system

3

2

Assessment (includes both continuous and summative assessment) a) Final Examination: 60% b) Practical Lab Assignment: 25% c) Written Assignment: 10% d) Presentations/Discussions: 5%

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CE/CZ 4001 Virtual and Augmented Reality