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Overview

Research in this discipline includes:

  • computer vision
  • machine learning
  • pattern recognition
  • signal processing.

We develop systems that can:

  • extract meaning
  • identify underlying structures
  • infer
  • recognise people and their activities across a variety of environments.

Our experts

Our discipline brings together a diverse team of experts who deliver world-class education and achieve breakthroughs in research.

Explore our staff profiles to discover the amazing work our researchers are contributing to.

Meet our experts

Professor Wageeh Boles
Position
Professor
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research field
Artificial Intelligence and Image Processing
Email
Professor Clinton Fookes
Position
Professor
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research field
Artificial Intelligence and Image Processing
Email
Associate Professor Bouchra Senadji
Position
Associate Professor
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Electrical and Electronic Engineering
Mechanical Engineering
Email
Dr Jacob Coetzee
Position
Snr Lecturer Electrical Engineering
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research field
Electrical and Electronic Engineering
Email
Dr Dhammika Jayalath
Position
Senior Lecturer in Electrical Engineering
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Electrical and Electronic Engineering
Communications Technologies
Curriculum and Pedagogy
Email
Dr Jasmine Banks
Position
Lecturer
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Artificial Intelligence and Image Processing
Computer Hardware
Electrical and Electronic Engineering
Email
Dr Simon Denman
Position
Senior Research Fellow
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Artificial Intelligence and Image Processing
Electrical and Electronic Engineering
Email
Dr Kien Nguyen Thanh
Position
Research Fellow
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Computation Theory and Mathematics
Electrical and Electronic Engineering
Email
Dr Sabesan Sivapalan
Position
Research Fellow
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Email
Dr Ivan Himawan
Position
Research Project Coordinator
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Artificial Intelligence and Image Processing
Information Systems
Electrical and Electronic Engineering
Email
Mr Mohammad Mahfujur Rahman
Position
QUT Postgraduate Research Award (QUTPRA)
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Email
Professor Vinod Chandran
Position
Adjunct Professor
Division / Faculty
Vision and Signal Processing,
School of Electrical Engineering, Computer Science
Research fields
Artificial Intelligence and Image Processing
Electrical and Electronic Engineering
Email

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Research

Our research focuses on computer vision, machine learning, pattern recognition and signal processing.

Vision is one of the most important contributors to automation, and we're leaders in building systems that automatically interpret visual scenes.

The algorithms and computational principles of vision, which are a key part of our research, also underpin many fields of autonomous vision, including computer vision and robotic vision.

We have applications in diverse areas, including:

  • aerial image processing
  • biometrics
  • cognitive radio
  • electromagnetics
  • human-computer interaction
  • medical imaging
  • speech processing
  • video search and retrieval
  • video surveillance
  • wireless communications.

Speech, Audio, Image, Video and Technology

Our researchers conduct postgraduate training, industrial consultancy and product development in the areas of speech, audio, image and video technologies.

A major focus of our research is in applying machine learning and pattern recognition techniques to solve real world problems in computer vision and speech and language processing.

Find out more

Airports of the Future

The Airports of the Future research project aims to improve the safety, security, efficiency and passenger experience within Australian airports.

Our researchers are looking into Intelligent Surveillance, using multi-camera networks to efficiently highlight patterns of interest to security personnel.

Find out more

Projects

Solve it or ignore it? The challenge of alignment distortion and creating next generation automatic facial expression detection

Project leader

Emeritus Professor Sridha Sridharan

Dates

2014-2016

Project summary

The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive.

Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world's largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.

The next generation speaker recognition system

Project leader

Emeritus Professor Sridha Sridharan

Dates

2013-2016

Project summary

The next generation of speaker recognition technologies developed through this project will enable secure person authentication by voice in financial transactions and benefit the community through the elimination of identity fraud. This project will safeguard Australia by identifying criminal suspects using their voice and combat terrorism by using voice to locate and track terrorists.

Interdisciplinary projects

Improving productivity and efficiency of Australian airports – a real time analytics and statistical approach

Project leader

Associate Professor Clinton Fookes

Dates

2014-2017

Project summary

Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity. However, complex dependencies and differing operational objectives complicate this task.

This project aims to develop a real-time, whole-of-system operational performance framework that can help operators in finding and evaluating solutions to maximise throughput, reduce wait times and mitigate flow-on effects. Innovative new video analytic and Bayesian Network based tools are integrated to address the challenges of adaptability and uncertainty.

Monitoring intuitive expertise in the context of airport security screening

Project leader

Associate Professor Clinton Fookes

Dates

2015-2017

Project summary

During airport security screening and processing, confusion and error are greatest when systems or contexts are unfamiliar. Poorly designed systems compromise the interactions of airport security personnel and decrease their ability to promptly and accurately respond to situations.

This project aims to deliver a suite of automated methods to monitor security operator knowledge and engagement, to assess the real-time security screening context, and to detect unusual passenger behavior at the screening check-point. This monitoring aims to provide new knowledge and techniques to enhance security operator performance, refine the screening process, improve passenger experience and, most critically, ensure safety at Australian airports.

View our student topics

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