Scientific Projects

The MPLab laboratory is involved in the joint project SCOPIA where the task of our colleagues is to develop accurate image registration techniques for multi-spectral images:   Predicting the chances of a successful Embryo transfer by the use of minimal invasive endoscopic device

European Defence Agency Ad-Hoc Research and Technology Category B Project
2014/12-2017/12

Based on the APIS project, with extended goals: "To study, define, analyse a new system concept for implementing and demonstrating ISAR imaging capability in a plug-in multistatic array passive radar finalized to target recognition."

DUSIREF (Dynamic Urban Scene Interpretation and REconstruction through remotely sensed data Fusion) is a joint project of the Distributed Events Analysis Research Laboratory (DEVA) of MTA SZTAKI and Infoterra-Astrium GeoInformation Services Hungary, funded by the European Space Agency (ESA) under the PECS-HU framework. The main objective of the project is high level urban scene recognition and change interpretation based on heterogeneous Remote Sensing (RS) data sources (mainly optical and TerraSAR satellite images and LIDAR data).

The main goal of ProActive is to research a holistic citizen-friendly multi sensor fusion and intelligent reasoning framework enabling the prediction, detection, understanding and efficient response to terrorist interests, goals and curses of actions in an urban environment.To this end, ProActive will rely on the fusion of both static knowledge(i.e. intelligence information) and dynamic information (i.e. data observed from sensors deployed in the urban environment).

The integrated4D (i4D) project of MTA SZTAKI is a joint mission of the Distributed Events Analysis Research Laboratory (DEVA) and the Geometric Modelling and Computer Vision Laboratory (GMCV). The main objective of the project is to design and implement a pilot system for the reconstruction and visualisation of complex spatio-temporal scenes by integrating two different types of data: outdoor 4D point cloud sequences recorded by a car-mounted Velodyne HDL-64E LIDAR sensor, and 4D models of moving actors obtained in an indoor 4D Reconstruction Studio.

Earth observation is a growing field of interest in various application areas, such as monitoring agricultural activity, detection of pollution and environmental crimes, management of urban area expansion, crisis management, including civil protection, or homeland security. However, the evaluation of the collected remotely needs exhausting human intervention up to now due to the rich and continuously augmenting content and various aspects of assessment. For this reason, necessity of automated recognition problems in remote sensing is raised by both national and international demands.

The work will focus on the research of indexing, retrieval and visualization schemes for searches over large video pools. The main goals of this research could be summarized as the following:

When we apply sensors to measure a workspace, we can meet some interesting questions about the information content of he examined system:
   * How can we estimate that something important happened in that space?
   * Can we estimate the degree of freedom of the space of events?
   * Measuring the events in the space, can we estimate the effect of an external impact?
   * If we directly manipulate some processes in the events’ space, can we measure the effect? Meaning that we want to measure the change in the events' process affected by the intrusion.