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The objective of the presented approach is to develop a 3D-reconstruction method for micro organisms from sequences of microscopic images by varying the level-of-focus. The approach is limited to translucent silicatebased marine and freshwater organisms (e.g. radiolarians). The proposed 3D-reconstruction method exploits the connectivity of similarly oriented and spatially adjacent edge elements in consecutive image layers. This yields a 3D-mesh representing the global shape of the objects together with details of the inner structure. Possible applications can be found in comparative morphology or hydrobiology, where e.g. deficiencies in growth and structure during incubation in toxic water or gravity effects on metabolism have to be determined.
GL-Wrapper for Stereoscopic Rendering of Standard Applications for a PC-based Immersive Environment
(2007)
Augmented Perception - AuPer
(2004)
The objective of the FIVIS project is to develop a bicycle simulator which is able to simulate real life bicycle ride situations as a virtual scenario within an immersive environment. A sample test bicycle is mounted on a motion platform to enable a close to reality simulation of turns and balance situations. The visual field of the bike rider is enveloped within a multi-screen visualization environment which provides visual data relative to the motion and activity of the test bicycle. This implies the bike rider has to pedal and steer the bicycle as they would a traditional bicycle, while forward motion is recorded and processed to control the visualization. Furthermore, the platform is fed with real forces and accelerations that have been logged by a mobile data acquisition system during real bicycle test drives. Thus, using a feedback system makes the movements of the platform reflect the virtual environment and the reaction of the driver (e.g. steering angle, step rate).
This paper describes adaptive time frequency analysis of EEG signals, both in theory as well as in practice. A momentary frequency estimation algorithm is discussed and applied to EEG time series of test persons performing a concentration experiment. The motivation for deriving and implementing a time frequency estimator is the assumption that an emotional change implies a transient in the measured EEG time series, which again are superimposed by biological white noise as well as artifacts. It will be shown how accurately and robustly the estimator detects the transient even under such complicated conditions.
The work being described in this paper is the result of a cooperation project between the Institute of Visual Computing at the Bonn-Rhein-Sieg University of Applied Sciences, Germany and the Laboratory of Biomedical Engineering at the Federal University of Uberlândia, Brazil. The aim of the project is the development of a virtual environment based training simulator which enables for better and faster learning the control of upper limb prostheses. The focus of the paper is the description of the technical setup since learning tutorials still need to be developed as well as a comprehensive evaluation still needs to be carried out.