In this report the Computer Vision System toolbox of MATLAB® and the Visual Structure from Motion software are evaluated on three datasets of airborne imagery.
Our scientific and technical publications are an important vehicle for the dissemination of our work.
We have several goals for our publications:
- To communicate the results of the research program to clients and fulfil our reporting responsibilities to the Department of Defence.
- To record the results of our research program.
- To communicate the results of scientific research and technical information to Australian industry and academia.
- To increase awareness of and enhance the reputation of DST Group.
Latest scientific publications
This report describes the core foundational concepts of aerospace modelling, an understanding of which is necessary for the analysis of complex environments that hold many entities, each of which might employ a separate reference frame and coordinate system.
Epoxies are the most widely used resins for bonded composite repair; however they possess low fracture toughness, impact strength and peel strength due to high cross linking densities. In this work, the impact of two commercially available tri-block copolymers on the mechanical performance of two different low temperature cure epoxy resin systems are evaluated.
The Estimote Location BeaconTM is the latest addition to the Hybrid.Beacon DST Group project. This Technical Note will focus on one of the Beacon’s sensors, its ambient light capability.
This report addresses the description and MATLAB implementation of the Scale-Invariant Feature Transform (SIFT) algorithm for the detection of points of interest in a grey-scale mage.
This report addresses the description and implementation of numerical algorithms for the reconstruction of world points representing a scene, and pinhole camera poses from the scene images.
This report addresses the mathematical and numerical modelling of heat exchange in a solid object with the effect of thermal radiation included.
This report describes an algorithm that introduces new discretisation levels to support the representation of low probability values in the context of Bayesian network anomaly detection.