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Augmented Reality (AR) involves the real time registration of computer generated imagery to augment the information available within a real world scene.
Feature extraction and matching is a traditional method for shape matching and analysis.
The development and use of medical virtual environments is one of the major research themes within RIVIC.
The unit work with projects where imaging and visualization technologies can provide added value to medical applications.
This project attempts to develop efficient techniques for the representation and matching of 3D shapes.
Images of objects (such as a rotating teapot, views from a camera mounted on a robot, an actor illuminated from different positions on a hemisphere, etc.)
The captured either 2D or 3D data are usually unavoidably corrupted by imaging noise.
While the laser scanning systems usually have limited field of view, the captured data from a single viewpoint can only cover a part of the area of interest.