Learning to see in 3D. The project aims to endow machine vision with an ability we, as humans, use almost constantly: to judge 3D properties from a 2D image. This extremely useful ability will be applied to digital images to obtain 3D measurements and aid in automating tasks such as mining, surveying, medical diagnosis, and visual effects in movies.
Recognising and reconstructing objects in real time from a moving camera. This project will use a moving camera to estimate the three-dimensional shape and identity of objects and surfaces it can see. This ability, which we humans use all the time, has wide application in automation including driver assistance, exploring hazardous environments, robotics, remote collaboration, and the creation of three-dimensional models for entertainment.
Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result giv ....Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result given the input data in a short amount of time. The expected outcomes would support the construction of reliable and accurate computer vision-based systems, such as large-scale 3-D reconstruction from photo collections, self-driving cars and domestic robots.Read moreRead less
Active multispectral computer vision for defence and security. This project will develop new techniques to extract intelligent information from multispectral images in the visible and near infra-red spectrum. It will enable computers to automatically recognise objects, faces and human actions with unprecedented accuracy.
Person identification from multiple non-invasive iris and face biometrics in video. This project will undertake research to develop a prototype system for personal identification that can be used by law enforcement and security agencies to enrol people at points of entry at public places. The system will non-invasively acquire face and iris biometrics and match them against a database of known persons. The proposed system can be used in sensitive buildings for access control, eliminating the nee ....Person identification from multiple non-invasive iris and face biometrics in video. This project will undertake research to develop a prototype system for personal identification that can be used by law enforcement and security agencies to enrol people at points of entry at public places. The system will non-invasively acquire face and iris biometrics and match them against a database of known persons. The proposed system can be used in sensitive buildings for access control, eliminating the need to carry access cards or remember passwords. This research contributes to the national research priority of Safeguarding Australia. We will develop new techniques in computer vision and train new researchers in this area.Read moreRead less
Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-im ....Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-image understanding cannot be tackled similarly because the number of possible combinations of objects is too large. The project thus proposes a graph-based generalisation of the CNN approach which allows scene structure to be learned explicitly. This would represent an important step towards providing computers with robust vision, allowing them to interact with their environment.Read moreRead less
Integration of Spatiotemporal Video Data for Realtime Smart Proactive Surveillance. This project will have a great impact on the national security by helping the law enforcement agencies to stop crime before it happens. It will automatically detect and tag criminal activities in surveillance videos. It will detect, authenticate, track and profile individuals in sensitive installations. At airports, it will match faces to electronic images embedded in passports. The system will use existing surve ....Integration of Spatiotemporal Video Data for Realtime Smart Proactive Surveillance. This project will have a great impact on the national security by helping the law enforcement agencies to stop crime before it happens. It will automatically detect and tag criminal activities in surveillance videos. It will detect, authenticate, track and profile individuals in sensitive installations. At airports, it will match faces to electronic images embedded in passports. The system will use existing surveillance infrastructures for locating lost people and will also ensure privacy protection of public. On the commercial side, this project can recognize old customers for better and customized services. It can count the number of people present in each floor of a building for rescue operations and for designing future buildings.Read moreRead less
Automated Determination of the Pose of a Human from Visual Information - Markerless 3D Pose Recovery of Humans from Videos. The development of 3D human pose recovery has been sought by computer vision researchers for many years. Our results will, firstly, have benefit for Australia's standing in the international computer vision community. Over time, the research outcomes will be developed into a software product for rehabilitation analysis by recognizing discrepancies between the walking pat ....Automated Determination of the Pose of a Human from Visual Information - Markerless 3D Pose Recovery of Humans from Videos. The development of 3D human pose recovery has been sought by computer vision researchers for many years. Our results will, firstly, have benefit for Australia's standing in the international computer vision community. Over time, the research outcomes will be developed into a software product for rehabilitation analysis by recognizing discrepancies between the walking patterns of healthy individuals and those with abnormalities as a result of accidents or diseases. The Australian economy will benefit by the reduction in the lifetime cost of injuries. This software will also provide benefits to the movie animation, computer games industry, and the training of athletes.Read moreRead less
Unified Representations of Multimodal Biometrics for Robust Authentication and Identification. We propose two biometric systems based on two novel unified multimodal biometric representations. These systems will have a great potential impact on the national economy by reducing frauds related to identity, credit card transactions, and ATM withdrawals. Statistics show that these types of frauds are dramatically increasing in the U.S.A., the U.K., and Australia. Our systems will also have governmen ....Unified Representations of Multimodal Biometrics for Robust Authentication and Identification. We propose two biometric systems based on two novel unified multimodal biometric representations. These systems will have a great potential impact on the national economy by reducing frauds related to identity, credit card transactions, and ATM withdrawals. Statistics show that these types of frauds are dramatically increasing in the U.S.A., the U.K., and Australia. Our systems will also have government applications and will impact on the national security in areas related to immigration, passport and driver's license controls. Forensic applications include criminal identification, crime scene investigation and corpse identification (as in the case of the victims of the Asian tsunami 2004). Read moreRead less
An automated 3D model-based object recognition system. A novel, practical 3D vision system is proposed as a platform for fundamental applied research in 3D data acquisition, object modelling and object recognition. The significance of the vision system lies in the advancement of knowledge in three key areas of computer vision, registration, recognition and error propagation. The result is a system capable of sensing, modelling and identifying arbitrarily shaped free-form objects in a scene, an a ....An automated 3D model-based object recognition system. A novel, practical 3D vision system is proposed as a platform for fundamental applied research in 3D data acquisition, object modelling and object recognition. The significance of the vision system lies in the advancement of knowledge in three key areas of computer vision, registration, recognition and error propagation. The result is a system capable of sensing, modelling and identifying arbitrarily shaped free-form objects in a scene, an attribute lacking in current systems. Such a system can provide substantial economic benefits to industrial procedures such as grasp planning and quality control.Read moreRead less