Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions.
A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by co ....Robust face detection and recognition for computer-based security surveillance. The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions.
A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by collecting incremental face exemplars. The result of the research will be an algorithm that can improve its performance on-line adapting in a stable learning process each identity model to the correct facial examples.
The research has significant practical implication in visual surveillance increasing the robustness of identification of person identity, state and intent.
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Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being ....Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being privacy preserving, providing new avenues for the production of novel, socially acceptable products for aged care monitoring. Our methods spearhead future advancement in diverse disciplines due to the wide applicability of the methods to other sensor networks (Square Kilometre Array) and data types, providing new frameworks for addressing crucial problems of data management. Read moreRead less
Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effec ....Methodologies for automatic visual identification in heat detection aids. New techniques will be designed and developed to automate the existing manual heat detection of cattle, under general imaging conditions. The proposed intelligent system will consist of six stages: 1- image acquisition, 2- image preprocessing, 3- presence detection, 4- illumination compensation, 5- HD detection, and 6- heat detection. The proposed system will handle various image variations, and will be fast and cost-effective. The developed system will improve the productivity of Australian cattle industry.Read moreRead less
Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise deve ....Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise developed from the project will provide a competitive edge for Australian industries in aerospace, oceanography, robotics, remote sensing, and biomedical engineering. Read moreRead less
Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification.
Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations.
The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created
the possibility of performing the calculation ....Fruit shape estimation from stereoscopic images in real time. The research aims at improving the process of automatic fruit inspection and classification.
Existing stereo vision algorithms to extract depth information are unsuitable for real time calculations.
The increasing complexity and reducing cost of field programmable gate arrays along with the development of algorithms that have a high degree of parallelism and locality has created
the possibility of performing the calculations required in real time.
This projects aims to investigate the suitability of the various stereo vision algorithms available in the literature for real time hardware implementation with application to fruit shape estimation it real time.
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Visual intelligence for safe vehicle operation in industrial environment. Visual intelligence for safe vehicle operation in industrial environment. This project aims to develop safety devices for loosely constrained environments with public access, building on visual-based collision avoidance technology in controlled industrial settings. Increasing productivity in industrial workplaces creates a need for faster industrial vehicles. At fruit and vegetable markets and construction sites, forklift ....Visual intelligence for safe vehicle operation in industrial environment. Visual intelligence for safe vehicle operation in industrial environment. This project aims to develop safety devices for loosely constrained environments with public access, building on visual-based collision avoidance technology in controlled industrial settings. Increasing productivity in industrial workplaces creates a need for faster industrial vehicles. At fruit and vegetable markets and construction sites, forklift drivers, crane operators and crews are under pressure to move faster. The need for higher speed and the enormous human and financial cost of unsafe operations create opportunities for the deployment of intelligent safety devices. The expected outcomes of this project are safer public industrial environments, reductions in work related injuries, injury compensation costs and associated societal burdens.Read moreRead less
Intelligent collision avoidance system for mobile industrial platforms. This project will develop a collision prevention system for mobile industrial platforms that enhances existing artificial vision perception systems to mimic human eye capabilities. The outcomes of this project will result in significant reductions in work related injuries, injury compensation costs and associated societal burdens.
Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of grea ....Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of great importance to Australia's security and safety. The outcome of this research will provide the first steps towards formulating the next generation recognition systems that will improve the suitability of the face recognition for use in security, surveillance, intelligent robotics, banking, and smart environments.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100156
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Computational infrastructure for machine learning in computer vision. The many trillions of images stored on computers around the world, including more than 100 billion on Facebook alone, represent exactly the information needed to develop artificial vision. All we need do is extract it. This project will develop the computational infrastructure required to allow Australian researchers to achieve this goal.