Multiview video coding using cuboid data compression. This project investigates novel approaches to multiview video coding that use new data compression techniques and explicit occlusion handling. These new approaches complement the state-of-the-art, improving interactivity with instantaneous view change and VCR functionality, reducing encoding complexity, and increasing compression efficiency.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0775747
Funder
Australian Research Council
Funding Amount
$160,000.00
Summary
Distributed Medical Image Analysis and Visualisation Engine (MedVis). Improved understanding of neurological processes is crucial to improving clinical outcomes for patients. MedVis will contribute in three ways: support development of new methods of interpretation and analysis of complex neurological studies, allowing current methods to be applied more efficiently, and enabling distributed simulations and visualisations in real-time from remote sites.
The leading-edge, grid-based, software and ....Distributed Medical Image Analysis and Visualisation Engine (MedVis). Improved understanding of neurological processes is crucial to improving clinical outcomes for patients. MedVis will contribute in three ways: support development of new methods of interpretation and analysis of complex neurological studies, allowing current methods to be applied more efficiently, and enabling distributed simulations and visualisations in real-time from remote sites.
The leading-edge, grid-based, software and computational techniques developed for the project will enable visualization, analysis and modelling of massive volumes of image and other visualisation data. This capability is important in medical research where large visualisation data volumes are being created and studied by experts remote from each other.
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Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those ....Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc. Read moreRead less
A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.
Discovery Early Career Researcher Award - Grant ID: DE120101778
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Building change detection and map update using multispectral imagery and height data. This project will produce an effective building change detection procedure and a digital building map. Automatic building detection assists in taking possible precautions during natural disasters, whilst automatic building change detection facilitates an effective and efficient management of affected areas during and after the calamity.