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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.

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.

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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.

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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

Our topics

Are you looking to study at a higher or more detailed level? We are currently looking for students to research topics at a variety of study levels, including PhD, Masters, Honours or the Vacation Research Experience Scheme (VRES).View our topics

Our experts

We host an expert team of researchers and teaching staff, including Head of School and discipline leaders. Our discipline brings together a diverse team of experts who deliver world-class education and achieve breakthroughs in research.

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