Research Projects (2009)
- Show Keywords
- 3D Computer Vision 3D reconstruction Aerial Vision Augmented Reality Augmented Video Best Paper Award Biometrics Caleydo Computer Graphics Computer Vision Convex Optimization Coordinate transformations detection face Fingerprint Georeferencing GPU GUI HOG Human Computer Interaction Image Labelling Industrial Applications Information Visualization integral imaging Interaction Interaction Design Machine Learning Medical computer vision Medical Visualization Mixed Reality Mobile computing Mobile phone Model Multi-Display Environments Multiple Perspectives Object detection Object recognition Object reconstruction Object Tracking On-Line Learning Robotics Segmentation Shape analysis shape from focus SLAM Software Projects Structure from Motion Surveillance SVM Symmetry Tracking Fusion Tracking, Action Recognition User Interfaces Variational Methods Virtual reality and augmented reality Visual Tracking Visualization
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OUTLIER
(details) |
The ever increasing number of cameras in surveillance system requires automatic video analysis in order to spot critical situations and to alert the monitoring personnel in a timely manner. While most current approaches in this area aim for detecting a large number of specific events on a large set of complex application scenarios, the goal of this project is to go far beyond state of the art by developing novel online learning methods to detect unusual situations in a camera specific scenario. We will exploit the huge amount of data available for a specific camera to reliably learn usual and unusual situations. In particular the OUTLIER project will carry out basic research in the following areas:
These generic learning algorithms will be applied for the detection of unusual situations in public places and traffic scenarios. Examples are the detection of unusual crowd behavior (upcoming panic, barred emergency exits, or toppled persons), suspicious behavior of pedestrians (e.g. going from one car to another, loitering), vehicles or persons moving on unusual locations, the detection of unusual types of moving objects and detection of unusual situations like accidents, clashes and collisions. Unlike other approaches we do not want to model these situations explicitly and individually, but we will resort to learning to discriminate the usual situation from the unusual one. Research partners in the project are JRS, TUG for basic and applied research and Siemens for industrial exploitation of project results. |
2009 | 2011 |
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Multimedia Documentation Lab
(details) |
The potential for integration of multimedia content into the analysis of security relevant affairs is researched for the first time within the scope of Austrian security research efforts. The project’s goal is to harvest audio-visual information from specified open multimedia sources such as TV broadcasts and allow for integration into existing environments at user sites. The intended use of the system is to allow experts to efficiently generate more realistic and high-quality situation reports in the face of critical situations. Subsequently, these can be employed for communication with the population of Austria and to increase its security and sense of security - target goals of the KIRAS framework. An exemplary implementation of a prototype will be installed at the Zentraldokumentation of the Austrian Armed Forces. In terms of audio-processing the project builds upon existing technologies of the industrial partner, while the visual processing is investigated by ICG as academic partner and will mainly deal with person/face detection, tracking and recognition methods. |
2009 | 2011 |
