Global turmoil, terrorism and hybrid war has made cost-effective and energy-efficient surveillance of the critical infrastructure extremely important for public safety and critical functions. PROACTIF tackles the challenge by developing unmanned...
Efficient environment perception and reconstruction: Simplifying and compressing point clouds without the loss of meaningful information
Department in charge
In today's autonomous world, the transmission and interpretation of large amounts of information describing the environment is a key issue. The research aims to make self-driving cars, robots, and drones work more efficiently. This requires more...
B-prepared builds on a freely accessible massive collaborative knowledge base and data hub, demonstrating its usefulness via three demonstrator applications: a cooperative multiplayer VR serious game, simulating real disaster scenarios for the safest...
With technology rapidly enhancing and becoming more affordable, commercial and consumer drones have become increasingly popular since the beginning of the 21st century. They pose serious threats to safety (e.g. disturbances for airports and airplanes...
Scene analysis and reconstruction from incomplete spatial data
Department in charge
Due to the rapid progress of sensor technology, processing a large amount of incomplete 3D spatial data is becoming a critical issue. In environment perception tasks (e.g., remote surveillance, navigation of autonomous vehicles, medical diagnostics)...
Egy adott szenzorplatformról a vizsgált esemény értékelhető néhány leképzési eljáráson alapuló felismerési módszerrel, például mély-tanulási struktúrákkal. Ebben a folyamatban az adat / tulajdonság halmazt értékelő hálózatokon keresztül szemantikus...
Bring back to the engineering students the results of research activities in the field of digital manufacturing. Modeling, analysis, virtual and augmented reality, as well as the role of the human workers in the factories have been among the main...
Multimodal feature fusion for establishing novel 3D saliency models
Department in charge
The project aims to process the data of novel 3D sensors (e.g. Microsoft Kinect, Lidar, MRI, CT) available in a wide range of application fields and to fuse them with 2D image modalities to build saliency models, which are able to automatically and...
Numerous automotive and small aircraft companies have announced promising new applications in the field of autonomous vehicles. Alongside self-driving cars, in the near future small-size micro aerial vehicles could be used for goods delivery (Amazon...
The aim of the project is to develop an image fusion and processing method that uses images of cameras with different modalities to track various objects, taking into account the needs of border surveillance end-users. The project is financed by ESA...
Change detection and event recognition with fusion of images and Lidar measurements
Department in charge
The main goal of the project is to combine the newest 3D sensors with traditional high resolution cameras to obtain new pattern recognition, scene understanding event and change detection methodologies, extend the validity of the existing methods or...
Machine perception algorithms for self-driving vehicles
Department in charge
A projekt célja a közúti teherszállítás önvezetésének, ezen belül is elsősorban környezetérzékelésének fejlesztése volt. A projektben tehergépjárművekre szerelt környezetérzékelő szenzorok adatait feldolgozva valósított meg a Gépi Érzékelés...
