RTD activities in the next subareas of groundbreaking applications are performed
Smart multi-sensor signal and image processing;
Video-analytic technologies for multi-object identification, recognition, tracking,
behaviour estimation and event prediction;
Multi-object Data Fusion and Decision Making under Uncertainty, Conflicts or/and Paradoxes.
Multisensing considers a set of sensors of similar or different type, but jointly working to receive
more relevant and accurate information about observed objects. Smart multisensing has the potential to change
fundamentally the systems performance on the base of embedded information processing devices and their ability
to exchange information monitored in real time, what a simple sensor system could not give. Smart multisensing often
provides new information about the objects of interest by merging data, signals and/or images.
Space-Time Adaptive Processing (STAP) algorithms nearly developed for radar applications enable to develop advanced
and more effective algorithms for sound processing in acoustic holography. Data fusion theory reveals how to combine
efficiently information from multiple sources and sensors in order to achieve inferences in some sense better that single
source information. The advanced distributed computing paradigm allows also passing many of the milestones, encountered in
previous centralised sensor information processing architectures. The ability to monitor the scene of interest by variety of
sensors gives a colorful picture of observed objects, but many problems arise to be solved at the same time, like: multi-objects
multi-sensors detection, identification, classification and tracking; sensor data fusion; behaviour estimation
and event prediction; content based image retrieval; intelligent decision making under uncertainty, conflicts or/and paradoxes.
Video-analytic methodology is used to extract meaningful information from video data flow in order to detect, recognise
and track events of interest. The final goal is to achieve automatic behaviour estimation and early warnings of potential risks.
Our research is oriented to a number of innovative solutions, including:
3D scene reconstruction;
Development and testing of new approaches to some Biometrics problems like behavior analysis,
human-centered and multimodal interfaces based on eye tracking, facial expressions, etc.
Development of innovative approaches for fusion of uncertain, imprecise, highly conflicting attributes
data, encountered in sensors' signals, at various levels of abstraction. It is based on a new
Dezert-Smarandache theory for plausible and paradoxical reasoning and fuzzy logic;
Development of new algorithms for adaptive non-linear filtration, segmentation and interpretation
of gray-scale images in order to be used in non-destructive testing with ultrasound waves;
Development of new algorithms for space-time adaptive processing (STAP) in order to be applied
to acoustic holography with multi-element microphone arrays;
Development of video-analytic tools for 3D object identification and tracking on the base of information
from different types of sensors.
