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Ioannis Pitas
Researcher at Aristotle University of Thessaloniki
Publications - 826
Citations - 26338
Ioannis Pitas is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Facial recognition system & Digital watermarking. The author has an hindex of 76, co-authored 795 publications receiving 24787 citations. Previous affiliations of Ioannis Pitas include University of Bristol & University of York.
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Proceedings ArticleDOI
Appearance based object tracking in stereo sequences
TL;DR: A novel algorithm is proposed, that performs tracking of rigid objects in 3D videos, without knowledge of the camera calibration parameters, by exploiting only visual information obtained from the left and right video channels, namely luminance and disparity information.
Journal ArticleDOI
Towards a knowledge-based system for automated geophysical interpretation of seismic data (AGIS)
TL;DR: In this article, an expert system for geophysical interpretation of seismic reflection data is presented. But it is not shown how to perform a knowledge-based automated interpretation of the reflection data.
Proceedings ArticleDOI
2D visual tracking for sports UAV cinematography applications
TL;DR: Overall, it was found that state-of-the-art 2D visual trackers are dependable and fast enough to be used in drone cinematography, particularly when combined with periodic target re-detection.
Proceedings ArticleDOI
Motion field estimation by vector rational interpolation for error concealment purposes
TL;DR: Simulation results prove the satisfactory performance of the novel nonlinear interpolation schemes and the success of their application to the concealment of predictively coded frames.
Proceedings Article
The MOBISERV-AIIA Eating and Drinking multi-view database for vision-based assisted living
TL;DR: The human centered interface specifications and implementations for such a system, which can be supported by ambient intelligence and robotic technologies, are described and a multi-view eating and drinking activity recognition database that has been created in order to facilitate research towards this direction is described.