R&D
METIS R&D Project
“Multimodal machine learning and signal processing technologies from multiple heterogeneous information sources for safety applications and surveillance of critical infrastructures – METIS”, General Secretariat for Research and Technology (GSRT) funded project (T1EDK-01169)
Visit the METIS project websiteMultimodal machine learning for critical infrastructure surveillance
This project aims at developing signal processing, machine learning algorithms and frameworks for semantic information extraction (object detection and recognition, motion tracking, anomaly detection) from multiple heterogeneous information sources (RGB cameras, thermal cameras and various types of radars). It also aims at implementing multimodal information fusion techniques and, ultimately, at building an advanced decision support system for critical infrastructure safety and surveillance applications.
Given the heterogeneity of data flows originating from multiple different sensors, such as RGB cameras, thermal cameras and various types of radars (Long Range Radars, microwave barriers or tripwire microwave sensors), the project will develop pattern recognition and machine learning algorithms appropriate for the different data modalities.