Post on 04-Aug-2020
School of Information Technology
Updated: October 2015
CRICOS Provider Code: 00113B
2016
HONOURS PROJECTS
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2016 HONOURS PROJECTS
CRICOS Provider Code: 00113B Page 1
Table of Contents
Synthesis and animation of procedurally generated game characters ............................................... 3
Characteristics of dominance displays in multiplayer game environments ........................................ 3
Nox Transverse ..................................................................................................................................... 4
Protocol analysis tools to analyse well‐known communication security protocols ............................ 5
Architecture of Internet of Things (IoT): what are the challenges? .................................................... 6
Identify and model gene signatures to predict human behavioural activities .................................... 7
Develop an automatic computer aided finger spelling system for deaf people ................................. 7
Develop a marker less augmented reality system for human‐computer interaction ......................... 8
Evaluating student evaluation: online mathematics assignments ..................................................... 9
Bonferroni means: theoretical developments and applications in decision‐making .......................... 9
Deakin Game Mobile App .................................................................................................................... 9
Melbourne History Mobile App ......................................................................................................... 10
Travel Mobile App .............................................................................................................................. 10
Optimal kidney exchange planning for pools with altruistic donors ................................................. 10
Optimising wireless sensor network operations and/or military airborne vehicle operations ........ 11
The Diet Problem revisited ................................................................................................................ 11
Developing an Aggregated Ranking Ontology for Mainstream Sports .............................................. 12
Dota Analytics .................................................................................................................................... 12
Raspberry Pi ....................................................................................................................................... 13
Cloud‐based weather station using open‐sourced hardware ........................................................... 13
Facial Recognition using Point Cloud Models .................................................................................... 14
Automated recognition of successful feeding dives in Australasian Gannets .................................. 14
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Visual pursuit and evasion for drones ............................................................................................... 15
Who is Tweeting on Twitter: Human, bot, or cyborg? ..................................................................... 15
Security and privacy for social networks ........................................................................................... 16
Networking for big data applications ................................................................................................ 16
Psychology techniques in cybersecurity ............................................................................................ 16
Healthcare of using Kinect and smart application ............................................................................. 17
Research and development of internet traffic classification system ................................................ 17
Contact Us .......................................................................................................................................... 18
The School of Information Technology also offers students the opportunity to
propose their own research projects, or to suggest modifications to the suggested
projects above, so as to better align to individual learning objectives.
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Synthesis and animation of procedurally generated game characters Supervisor: Dr Shaun Bangay
Email: shaun.bangay@deakin.edu.au
Campus: Burwood
Procedural generation of game characters produces a large range of varied characters without the manual
effort required to produce each one. Previous approaches create surface meshes but these are no longer
sufficient for the demands of current applications. Previous Honours projects have:
Investigated building all the internal structures of the body as components from the inside out, layer by
layer. This approach provides valuable meta‐data specifying the purpose and parameters of each part of the
creature, which can be used for subsequent manipulation of the model.
Defined the development of the body as a grammar, progressively refining the structure in a way that
resembles development of the organism. This ensures that the complex internal structures are correctly
connected, and ensures that novel creatures are internally consistent.
We plan to continue with this line of research. Problems that still need to be solved include:
Converting a grammatical description of a creature into the corresponding geometry. Here suitable
representations need to be devised to suit the levels of deformation of the individual components (such as
bone, muscles, tendons, skin). A constraint satisfaction problem must be expressed and solved to ensure
that overlapping components are correctly placed. This goal would be validated by recreating the physical
structure of existing creatures from a grammatical description.
Automatically generating suitable gaits producing movements that allow the creature to move and interact
with its environment. This problem would be investigated by first reproducing a current state of the art
approach (such as that described in Igor Mordatch, Zoran Popović, and Emanuel Todorov. 2012. Contact‐
invariant optimization for hand manipulation. In Proceedings of the ACM SIGGRAPH/Eurographics
Symposium on Computer Animation (SCA ’12). Eurographics Association, Aire‐la‐Ville, Switzerland,
Switzerland, 137‐144).
Characteristics of dominance displays in multiplayer game environments Supervisor: Dr Shaun Bangay
Email: shaun.bangay@deakin.edu.au
Campus: Burwood
Previous studies of dominance displays (The Logic of Animal Conflict, J. MAYNARD SMITH & G. R. PRICE,
Nature 246, 15 ‐ 18 (02 November 1973)) have identified strategies involving mock battles as being stable
within populations under evolutionary pressures. Similar displays are being observed within multiplayer
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game environments, such as League of Legends, where players use taunting and gloating to dominate rivals
and conservative play strategies (grind) to optimize standing within the game community. This behaviour is
unexpected since these behaviours may forfeit opportunities for fun and epic wins and are unnecessary
given the non‐permanent nature of death in these games.
This project investigates the factors leading to the use of these strategies. After gathering data from a
number of games the research will use game theory to identify how evolutionary stable strategies arise in
these artificial environments. In‐game behaviour data will need to be collected and analysed to identify the
strategies employed by players and the statistical properties of payoffs that result. Communications
between players can be analysed to automatically extract features that describe various forms of dominance
display.
This process of investigation is intended to provide insight into questions such as:
Does team size have an effect on the level of dominance behaviour? This would require investigating
strategies employed in a range of games representing different player groupings. In particular, does this
effect change in teams where players know one another and play together frequently, compared to games
where teams are randomly assigned?
How does this dominance display change for different player demographics? These displays in nature are
associated with mating rights. Do factors such as age and gender of players and their audience affect the
extent to which they are demonstrated? Prestige and social acceptance are also potential factors that may
be linked to strategies that favour grind.
Do sexualized representations of characters affect this behaviour? There is anecdotal evidence that gamer
behaviour changes in the presence of a declared female. Some games also style characters differently in
other cultural regions affecting the extent to they are sexualized. These factors could be investigated with
the goal of relating them to dominance displays.
Nox Transverse Supervisor: Dr Shaun Bangay
Email: shaun.bangay@deakin.edu.au
Campus: Burwood
In a recent presentation the National Disability Insurance Scheme (NDIS) indicated that their funding focus is
shifting away from service providers and towards individuals directing spending towards products that they
personally regard as improving their lifestyle. There is now scope for producing a greater variety of devices
and software that can use innovative technologies to provide customized facilities desired to support specific
forms of disability.
Our recent work in augmenting players and their environment for the purposes of mobile active gaming
suggests some strategies that could be used to develop such products. Technology mediated physical
interactions allow varied forms of participation to be normalized so all participants can contribute equally to
play regardless of personal circumstances. Game play mechanics accommodate multiple sensory modalities,
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for example substituting audio cues for visual ones, and provide ways of achieving equivalent experiences
regardless of personal circumstances.
The projects investigates the sensing, communication, processing and interaction mechanisms that are
needed to produce disability agnostic interaction devices: the Nox Transverse (ideally to provide an
equivalent impact to the Occulus Rift). Aspects of this development would involve:
1. For a given sensory disability, investigate sensing technologies and signal processing mechanisms
that will provide equivalent information necessary to achieve specified goals (for example,
perceiving the position of players and other game obstacles in a physical environment).
2. Develop algorithms to perform processing required to translate one sensory modality into another
and incorporate that as a game mechanic. Our previous research in using audio cues to provide
visual information can serve as a starting point.
Protocol analysis tools to analyse well‐known
communication security protocols (Special attention to sensory protocols)
Supervisor: Dr Morshed Chowdhury
Email: morshed.chowdhury@deakin.edu.au
Campus: Burwood
Security protocols and their communication flows are often exploited by intruders to discover vulnerabilities
of robust distributed systems. Many of the popular security protocols are mathematically modelled and
analysed before implementation. They were further analysed after implementing. However, mathematically
modelling to verify security claim of protocols are error prone as mathematically modelling require to use
many inference rules. Some of these modelling are based on incorrect assumptions too. Analysing a security
protocol after implementing to a live system is expensive. It also may be too late to discover vulnerabilities
and infeasible to adapt without changing the entire system. This project is aim to investigate on available
automated security protocol’s claim verification tools and their activities. It then further investigate to find
out two tools among available one’s that can be used to verify security claims of wireless and wired security
protocols for distributed system like IoT. Finally the investigators will model and analyse some well know
security protocols with their appropriate adversary model using identified automated security claim
verification tools. By analysing they will compare and contrast their findings on
Appropriateness of the tools and their capabilities for proactive security claim verification
Does the identified vulnerabilities on analysed protocol exist or it’s a false positive?
What are the shortcomings of available automated security claim verification tools?
Methodological approach: Students are expect to first investigate existing information related automated
security claim verification tools. They then need to select two best tools (robustness and accuracy) based on
available information in the literature. The proponents need to setup these two tools and prepare a user guide
for the same. To test their functionality, proponents need to select few well known security communication
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protocols such as DTLS and so on and model them with their appropriate adversary models. Students will then
analyses the models using automated security claim verification tools to compare and contrast between tools
and their analysis on selected protocols outcome.
Necessary skills / knowledge: Basic knowledge of Linux OS, programming and security communication
protocols
Architecture of Internet of Things (IoT): what are the challenges? Supervisor: Dr Morshed Chowdhury
Email: morshed.chowdhury@deakin.edu.au
Campus: Burwood
There is a big debate to name recent development of distributed computing that supports communication
between things (mainly machine to machine and objects to objects) that permits easy connectivity, control,
communications, and useful applications for and between things. Many people are naming it as the Internet
of Things, however others are naming it the Internet for Things. Lack of understanding and standardization
about IoT architecture has fuelled this debate. How will these objects interact in and across applications? Many
times, things or sets of things must be disjoint and protected from other devices. At other times, it makes
sense to share devices and information. To move forward towards a feasible security solution for Internet of
Things and achieve secure Internet of Things implementation a reality, a standardized structure of Internet of
Things is a very important key steps. In this project, student will investigate state of the art about architectural
approaches of Internet of Things. The proponent to identify issues to standardized and unify IoT architecture.
The project aim to address followings:
Evaluate current proposal of Internet of Things structure in literature.
Identify current challenges to standardized the Internet of Things structure for security research and
development
Methodological approach:
Student expects to investigate relevant literature about IoT structure and then compare and contrast
them. The student then identify challenges to standardized IoT structure for security research and
secure deployment. The proponent need to do comparative study of different IoT architecture which
are already proposed in the literature using a modelling tool (such as OPNET or NS2) or hardware
(known as VIPER: the Python IoT Design suite for Arduino, UDOO & Spark) based implementation.
Necessary skills / knowledge: Willing to learn an appropriate modelling tool and/or software in windows or
Linux
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Identify and model gene signatures to predict human behavioural activities Supervisor: Dr Morshed Chowdhury
Email: morshed.chowdhury@deakin.edu.au
Campus: Burwood
Human activities and behaviours are influenced by their gene structure and contextual influence that effect
hormonal secretion. A great deal of research is dedicated to identify the model or structure of gene signature
to forecast different deadly diseases. Many researchers have also worked on to identify responsible gene
signatures that influence human behaviour. However, no gene model or responsible Gene signature identified
to explain human behavioural activities. Moreover, little research were done to actually forecast human
behavioural activities using gene signatures. Therefore, research to identify human behaviour using gene
signature is an established but still pre‐mature research area. Very little or no research is conducted to
combine gene structure and contextual influence to forecast human behavioural activities. In this project,
student will investigate to determine current state of work for predicting human behaviour based on gene
signature. In addition, student will work on data set of different type of contextual influences that effect
hormonal secretions to influence human behaviours. The project aim to address followings:
What is the current state of art to predict human behavioural activities?
Compare and contrast between current methods.
Identify contextual influence that control hormone secretion.
Methodological approach: Student expects to first find relevant literature about gene signatures to
understand them. The proponent then further need to investigate existing literature and proposals to predict
human behaviours. Student then use a data analysis tool (such as MATLAB) to implement existing approaches
to compare and contrast among them. It will be productive to find an open source data repository to conduct
the study. Further study then need to be done to determine contextual parameters that effects hormonal
secretions that influence human behaviour.
Necessary skills / knowledge: Willing to learn and familiarize with the appropriate algorithm and tools to
conduct the analysis of Gene signature data.
Develop an automatic computer aided finger spelling system for deaf people Supervisor: Dr Morshed Chowdhury
Email: morshed.chowdhury@deakin.edu.au
Campus: Burwood
The aim of this research work is to develop an automatic computer aided system to help deaf people to
communicate with other people in their community. It is well‐known that the deaf people always
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communicate with a sign language used in their own country. Therefore recognition of sign language is an
important task for understanding the meaning of a sign used for giving an information. If a sign is not known
by the signer or the recipient for a particular word, it can be spelt out explicitly by finger spelling. In this
research work we are considering finger spelling, where Australian English words are spelt out gesturally
using Auslan Alphabet. Unlike general sign language recognition, finger spelling techniques consider only
static and dynamic characteristics of manual (gestures made with hands) features to recognise alphabet.
Student will introduce a new technique to recognise individual alphabet and combine them to form an
individual word.
Develop a marker less augmented reality system for human‐computer interaction Supervisor: Dr Morhsed Chowdhury
Email: morshed.chowdhury@deakin.edu.au
Campus: Burwood
The objective of this research project is to design and develop a human‐computer interactive system in
augmented reality environment in which human hands play a vital role to interact with the computer. The
interesting characteristics of augmented reality makes its usage in different industries like education and
game. In a traditional augmented reality environment, virtual objects appear on the display device based on
the designed marker placed in front of the camera mounted with the computer. An expected activity is
displayed on the monitor based the structure of the marker shown. Due to carry and design problems,
marker less augmented reality becoming popular day by day. For this reason bare hand can be used for
interaction in augmented reality environment. For making human computer system interactive, hand‐fingers
can play an important role because hand image structures can be changed and manipulated for different
numbers and positions of fingertips.
Aggregation functions and producer assessment
Supervisor: Dr Simon James
Email: simon.james@deakin.edu.au
Campus: Burwood
A ‘producer’ is evaluated both in terms of the number of products produced and the quality of those
products. Examples include our assessment of a researcher’s publication history based on the number of
publications and their quality (the number of times they are cited) however we could also think of examples
in ecology where a region’s biodiversity takes into account both the number of species present and the
abundances of those species. This project uses the framework of aggregation functions for addressing some
of the difficulties associated with this task such as comparing objects of different dimension.
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Evaluating student evaluation: online mathematics assignments Supervisor: Dr Simon James
Email: simon.james@deakin.edu.au
Campus: Burwood
With high student enrolments and budget constraints, universities more and more are turning to online
automated assessment. This project looks to determine whether such assessment can be effectively used
for first year mathematics classes. It will look both into how well the results of multiple choice/numerical
input tests are correlated with sets of example tasks solved by hand, and how students perceive the benefits
of using such methods, i.e. immediate feedback, time taken, technology etc.
Bonferroni means: theoretical developments and applications in decision‐making Supervisor: Dr Simon James
Email: simon.james@deakin.edu.au
Campus: Burwood
The Bonferroni mean takes the average of all input product pairs and allows us to ensure a number of
mandatory requirements are satisfied in decision making. There have been a number of recent extensions
and generalizations with potential applications in consensus and decision making, however the behaviour of
these functions is still not well understood.
This project aims to study the behaviour of various Bonferroni mean constructions, both theoretically and in
application.
Deakin Game Mobile App Supervisor: Dr Henry Larkin
Email: henry.larkin@deakin.edu.au
Campus: Burwood
This project involves the creation of a mobile app that involves Deakin campus in some form of game. The
platform can be iOS, Android or web app. The game type is open ended, and can be discussed with the
supervisor.
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Melbourne History Mobile App
Supervisor: Dr Henry Larkin
Email: henry.larkin@deakin.edu.au
Campus: Burwood
This project involves the creation of a mobile app that shows Melbourne as a map and allows the user to pull
up historic information on points of interest. The platform can be iOS, Android or web app.
Travel Mobile App Supervisor: Dr Henry Larkin
Email: henry.larkin@deakin.edu.au
Campus: Burwood
This project involves the creation of a mobile app that helps people when they travel. The project is fairly
open‐ended, and can be discussed with the supervisor. For example, the app could be a mobile app that
allows users to scan receipts via mobile camera, extract purchase + purchase cost, and store an
accumulation of the financial purchases recorded while they travel. The platform can be iOS, Android or web
app.
Optimal kidney exchange planning for pools with altruistic donors Supervisor: Dr Vicky Mak‐Hau
Email: vicky.mak@deakin.edu.au
Campus: Burwood and Cloud online
The Kidney Exchange Problem (KEP) is a combinatorial optimization problem with a number of variations.
Defined on a directed graph, the KEP has two variations: one concerns cycles only, and the other, cycles as
well as chains on the same graph. A vertex on the digraph represents a donor‐patient pair who are related
but with incompatible kidneys due ABO blood type incompatibility or positive serological cross match. A
kidney exchange pool contains multiple such incompatible pairs. In some cases, the donor of one pair can
donate his/her kidney to the patient of another pair should the kidney be compatible. If Donor As kidney is
suitable for Patient B, and vice versa, then there will be arcs in both directions between Vertex A to Vertex B.
Such exchanges form a 2‐cycle. There may also be cycles involving 3 or more vertices. As all exchanges in a
kidney exchange cycle must take place simultaneously (so as to avoid donors dropping out from the program
when his/her partner has obtained a kidney from another donor), due to logistic and human resource
reasons, only a limited number of kidney exchanges can occur at the same time, hence the cardinality of
these cycles are constrained. In recent years, kidney exchange programs around the world have altruistic
donors in the pool. A sequence of exchanges that starts from an altruistic donor forms a chain instead of a
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cycle. In this project, we will study the cycles‐ and‐chains KEP—the Cardinality Constrained Cycles and Chains
Problem (CCCCP) by exploring efficient solution methodologies and examining various integer‐programming
models.
Optimising wireless sensor network operations and/or military airborne vehicle operations Supervisor: Dr Vicky Mak‐Hau
Email: vicky.mak@deakin.edu.au
Campus: Burwood
Given a directed or undirected graph with vertex set V and arc set A, the Travelling Salesman Problem (TSP)
is a well‐studied combinatorial optimisation problem that concerns the finding of a tour that visits each
vertex exactly once, with the total travelling cost/time minimized.
The CETSP, however, does not require that the traveller visit every node at its fixed location. Rather, the
traveller can simply visit a node if it enters a compact neighbourhood set of the node.
The CETSP has applications in wireless sensor network operations, as well as military airborne vehicle
operations. This project is to study mixed‐integer linear programming models, exact methods, and heuristic
methods for the CETSP.
The Diet Problem revisited Supervisor: Dr Vicky Mak‐Hau
Email: vicky.mak@deakin.edu.au
Campus: Burwood
The Diet Problem is one of the first real‐life optimization problems studied. George Stigler was one of the
first researchers to come up with a near best solution of $39.93 per year (in 1939 prices). In 1947, Jack
Laderman of the Mathematical Tables Project of the National Bureau of Standards solved the problem using
the Simplex Algorithm (invented by Dantzig Wolfe). It took 120 man‐days to solve the 9‐equation 77‐
unknown problem, using hand‐operated desk calculators. The optimal cost is found to be $39.69.
Over the years, researchers have fallen out of love with the Diet Problem, and moved on to other new and
exciting combinatorial optimization problems. In this research project, we would like to revisit The Diet
Problem, as new nutritional knowledge has been gained since the 50’s, and new modeling and solution
techniques have been developed, e.g., integer programming and the branch‐and‐bound algorithm. With
these new techniques, we are able to design new models to handle realistic restrictions that were previously
impossible to be included.
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Developing an Aggregated Ranking Ontology for Mainstream Sports Supervisor: Dr Lei Pan Associate Supervisors:
Email: l.pan@deakin.edu.au Dr Tim Wilkin, Dr Simon James
Campus: Burwood
Contemporary sports have become an important part of the public life. Yet, the current schemes or methods
used to rank player or teams are developed to eliminate human bias by aggregating referees' verdicts,
historical performance, even geographical locations and so on. Such examples include how FIFA seeds the
world cup teams, how NBA decides the playoff schedules, how Olympic judges decide the winner of water
diving, and many more.
The current body of knowledge lacks a comprehensive ontology, which can be used to evaluate these
schemes across the board. This project aims to develop such ontology by surveying the aggregation schemes
used in mainstream sports.
The potential candidate should have fundamental mathematics knowledge in calculus and discrete math,
and have good interests in sports.
Dota Analytics Supervisor: Dr Lei Pan Associate Supervisor:
Email: l.pan@deakin.edu.au Dr Shaun Bangay
Campus: Burwood
Top Dota teams like TopSecret, Evil Geniuses, CDEC and EHome win millions of dollars per year as prize
money. Most game boards on the web provide merely statistical data on win rates and reliability measure on
tournament games where teams are duelled. These data are sufficient for amateur fans but offer little
insightful knowledge on team strategy, player style, player's preference on heroes and items. This missing
information is very valuable to build counter strategies for rival teams and to become training templates for
other players. By watching the match replay videos, analytics can be collected and developed: team strategy
‐‐‐ ban list, player choice sequence, hero pick, hero to player allocation; and in‐game tactics ‐‐‐ lane pick,
farming choice, items purchased and kills. The student investigator will derive analytics for one or two top
teams' performance in well‐known tournaments.
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Raspberry PiSupervisor: Dr Lei Pan Associate Supervisor:
Email: l.pan@deakin.edu.au Dr Shaun Bangay
Campus: Burwood
It is innovative! It is affordable! And it is Raspberry Pi.
Some cool project examples of Raspberry Pi can be found at https://www.raspberrypi.org/. Amongst these
examples, many are game application programs and others are related to robots. In fact, comparing with its
hardware capabilities, the software development is still in an infant stage.
The proposed project will investigate the software development issues of Raspberry Pi. Some key literature
references will be thoroughly discussed before identifying coding projects, proposing feasible designs and
developing prototypes. The developed prototypes may (but not limited to) be used in vehicles, toys,
classrooms and even your backyard. For example, smart farms, wild life observatories, car auto‐driving and
smart sensing systems.
The project has two aims: (1) evaluation of current software development model in the context of Raspberry
Pi; and, (2) design, implementation and testing on an actual Raspberry Pi. Raspberry Pi supports a good
range of programming languages ‐‐‐ ANSI C, C++, Python, C# and so on. Students with a major in computer
science or software development are encouraged to apply.
Cloud‐based weather station using open‐sourced hardware Supervisor: Dr Atul Sajjanhar
Email: atul.sajjanhar@deakin.edu.au
Campus: Burwood
The premise of Internet of Things (IoT) is the feasibility of machine‐to‐machine communication. IoT is
becoming increasingly popular because of the availability of internet‐enabled devices which offer a wide
range of applications. Further, open‐source hardware is cheap which contributes significantly to realising IoT
projects from concepts to fruition.
The proposed project will use open‐source hardware (Arduino Yùn board and sensors) to capture climate
data including temperature, humidity and barometric pressure, from the local‐environment. Data will be
uploaded to the cloud in real‐time and made web‐accessible. The web interface will present an interactive
time‐series visualisation of the climate dataset. The project outcomes are of interest to environmental
scientists; it will facilitate interrogation of the microclimatic contributions of the built environment,
especially urban heat island effects.
To undertake this project, you are expected to have sound programming knowledge and an understanding
of web technologies. The project will need programming skills in C and PHP.
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Facial Recognition using Point Cloud Models Supervisor: Dr Tim Wilkin Associate Supervisor:
Email: tim.wilkin@deakin.edu.au Dr Shaun Bangay
Campus: Burwood
Point clouds are spatial data sets generated by devices such as the Microsoft Kinect ™. They enable the
representation of surfaces of objects in terms of a set of discrete points in 3D space, containing additional
information such as colour. Such data sets provide for novel representations of surfaces beyond the texture
space or geometry space representations traditionally used in computer vision algorithms.
For automated facial recognition there are two competing approaches: those that identify faces within the
texture space of an image and those that use geometric features extracted from the image to identify the
subject. Ultimately, both use feature space representations built solely from 2D colour images, to determine
similarity of a test subject to known faces.
This project will explore the use of point cloud data of real human faces as the basis for facial recognition
using existing recognition algorithms. The focus will be on determining which of several competing strategies
provides the most robust recognition rates given factors such as subjects not looking at the camera, or noise
in the data set. The results from this research will feed into an ongoing collaborative project with the Faculty
of Health that aims to monitor subject’s television viewing behaviour using computer vision methods.
Automated recognition of successful feeding dives in Australasian Gannets Supervisor: Dr Tim Wilkin Associate Supervisor:
Email: tim.wilkin@deakin.edu.au A/Prof John Arnould (School of LES)
Campus: Burwood
Australasian gannets are the top avian marine predator in the waters south of Australia and thus,
understanding their feeding strategies and behaviours is vital to modelling the marine food chain and the
impact of gannet colonies on southern ocean fish stocks.
Gannets forage for food by diving headlong into the water from great heights to catch fish in their bills,
before resurfacing to consume their prey. Traditional methods for investigating foraging success rates
involve capturing birds and observing gut content. For many years Professpr Arnould has been equipping
Australasian gannets with devices that record flight telemetry and thus has a wealth of interesting and useful
data that can be used to develop an automated method for accurately and reliably identifying instances of
foraging success. Specifically, this project will investigate the design and training of an automated classifier
based on raw accelerometer data. This classifier will be evaluated against existing foraging records and,
ideally, will tested in the field to determine its viability as a novel tool for marine ecology research. This
research has the potential for a significant impact in marine ecology.
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Visual pursuit and evasion for drones Supervisor: Dr Tim Wilkin
Email: tim.wilkin@deakin.edu.au
Campus: Burwood
Small, light‐weight, agile drones (both fixed wing and multi‐rotor) are an ideal platform on which to explore
paradigms for visual pursuit and evasion for autonomous agents. In particular, operating these aircraft in
cluttered environments (both urban and natural) leads naturally to the problem of obstacle avoidance.
Traditional methods for avoidance rely either on specialised hardware sensors (such as lidar and sonar) or
computer vision algorithms. Visual obstacle avoidance is an open problem and one for which a good solution
will have a huge impact on both the hobby industries, as well as commercial and military applications of
autonomous aircraft.
This project will build upon results from a previous project supervised by Dr. Wilkin, which investigated
visual pursuit and evasion in discrete cluttered environments. In this project we will investigate the
automatic identification of visual clutter and the development of improvements to the existing algorithm to
perform automated real‐time generation of steering policies for both pursuit and evasion problems in
continuous environments.
Who is Tweeting on Twitter: Human, bot, or cyborg? Supervisor: Prof Yang Xiang Associate Supervisor:
Email: yang.xiang@deakin.edu.au Dr Jun Zhang
Campus: Burwood
Twitter is a new web application playing dual roles of online social networking and micro‐blogging. Users
communicate with each other by publishing text‐based posts. The popularity and open structure of Twitter
have attracted a large number of automated programs, known as bots, which appear to be a double‐edged
sword to Twitter. Legitimate bots generate a large amount of benign tweets delivering news and updating
feeds, while malicious bots spread spam or malicious contents. More interestingly, in the middle between
human and bot, there has emerged cyborg referred to either bot‐assisted human or human‐assisted bot.
This project aims to assist human users in identifying who they are interacting with by the classification of
human, bot and cyborg accounts on Twitter. The project has great interest to network and system security
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Security and privacy for social networks Supervisor: Prof Yang Xiang Associate Supervisor:
Email: yang.xiang@deakin.edu.au Dr Sheng Wen
Campus: Burwood
Social networks are websites designed for human interaction. People build social networks of contacts
bound by trust. The potential for mischief and malicious activities arises when one or more of those contacts
breaks your trust. When that happens, a number of misuses of social networks can happen, such as
compromising user account, malware propagation, insufficient use of privacy controls, etc. In this project,
you will investigate the most common areas of attack using social networks and find ways of minimising
risks. The goal of this project is to enable users to use social networks more safely.
Networking for big data applications Supervisor: Dr Shui Yu
Email: shui.yu@deakin.edu.au
Campus: Burwood
Big Data is a hot topic today, and it involves every section of human society with great applications.
Networking is a critical foundation for the forthcoming real Big Data applications. The expertise of
networking for Big Data is desperately desired by ICT industry and the research community. However, this is
a huge gap between the needs and the supplies.
In this project, we will explore the networking aspects for Big Data. The project involves both theoretical
studies and feasible implementations. For research oriented students, we will integrate existing
mathematical tools to tackle the problem, such as stochastic modelling, graph spectrum, even invent new
mathematical tools to meet the challenges in the emerging research field of Big Data. For industry oriented
students, we will focus on application perspective of Big Data, such as practical system design and
implementation on Hadoop.
The success of this project will train high quality HDR students for either academia or industry.
Psychology techniques in cyber security Supervisor: Dr Shui Yu
Email: shui.yu@deakin.edu.au
Campus: Burwood
Cyber security is a hot topic with pervasive applications nowadays. However, most of the existing methods
for cyber security are confined in the technology domain. In this project, we aim to initiate a brand new
methodology for cyber security by integrating the knowledge of both psychology and computer science.
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We will collaborate with staff from School of Psychology to work on real world problems. Psychology
knowledge will be integrated into cyber attack detection, mitigation, and traceback. Students are expected
to implement software prototypes, and demos as the outputs of the project.
As a cross discipline project, the knowledge and skills are highly expected by government agencies, industry,
and academia. The success of this project will position our students in an advanced place in either the job
market or PhD study.
Healthcare of using Kinect and smart application
Supervisor: Dr Jun Zhang
Email: jun.zhang@deakin.edu.au
Campus: Burwood
Kinect for Windows uses a set of technologies that enable humans to interact naturally with computers. The
free software development kit (SDK) provides developers with the foundation needed to create and deploy
interactive applications that respond to peoples’ natural movements, gestures, and voice commands. It
empowers developers to create innovative natural human computing solutions across a variety of areas.
This project aims to bring a healthcare solution to life by applying Kinect to monitor people’s posture. A
smart application will be developed to gently prompt every time people slouch to remind people to sit tall in
front of computer. The long‐term data of people’s posture will be stored in computer for further analysis
and health assessment. It’s not about drastic, life‐altering changes. It’s the simple, habit changes that can
truly improve people’s life. The combination of Kinect and application is the smart and powerful agent for
better posture, improved health and transformed appearance. Students will be supervised to apply C#
programming, computer vision and pattern recognition techniques in the research and development.
Research and development of internet traffic classification system
Supervisor: Dr Jun Zhang Associate Supervisors:
Email: jun.zhang@deakin.edu.au Prof Yang Xiang, Dr Yu Wang
Campus: Burwood
Internet traffic classification has drawn significant attention over the past few years. Classifying traffic flows
by their generation applications plays very important role in network security and management, such as
quality of service (QoS) control, lawful interception and intrusion detection [6]. Traditional traffic
classification methods include the port‐based prediction methods and payload‐based deep inspection
methods. In current network environment, the traditional methods suffer from a number of practical
problems, such as dynamic ports and encrypted applications. Recent research efforts have been focused on
the application of machine learning techniques to traffic classification based on flow statistical features.
Machine learning can automatically search for and describe useful structural patterns in a supplied traffic
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data set, which is helpful to intelligently conduct traffic classification. However, the problem of accurate
classification of current network traffic based on flow statistical features has not been solved.
This project aims to develop a new Internet traffic classification system. It will combine three existing traffic
classification techniques to accurately identify the origin of Internet traffic. Our research group has done a
lot of high quality research work on this important research topic. The honours student will get strong
support to implement a real‐world system and significantly improve research and development skills that
are preferable to work in academia and industry.
Contact Us
Dr Tim Wilkin
Honours Coordinator
Phone: +61 3 9251 7714
Email: tim.wilkin@deakin.edu.au
Ms Rosie Robertson
Course Advisor, Geelong
Phone: +61 3 5227 2536
Email: rosie.robertson@deakin.edu.au
Dr Vincent Kavenagh
Student and Staff Support Coordinator, Burwood
Phone: +61 3 9251 7451
Email: vincent.kavenagh@deakin.edu.au