PASSIVE ACOUTIC MONITORING: SOUNDS COME FROM HUMAN ENTITIES
The various acoustic sensors allows the detection and observation of various human activities in different environments.
A) Terrestrial Activities
Road Traffic
Deforestation Activities
B) Marine Activities
Boat Traffic:
C) Aerial Activities
References:
Z. Mnasri, S. Rovetta, F. Masulli “Anomalous Sound Event Detection: A Survey of Machine Learning Based Methods and Applications”, Multimedia Tools and Applications, December 2021.
Z. Mnasri, J. Giraldo, T. Bouwmans, “Anomalous Sound Detection for Road Surveillance based on Graph Signal Processing”, European Conference on Signal Processing, EUSIPCO 2024, 2024.
PASSIVE VISUAL MONITORING: MOVING OBJECTS COME FROM HUMAN ENTITIES
The various visual sensors allows the detection and observation of various human activities in different environments. From the terrestrial activities to the maritime activities, the visual sensors allow researchers to detect, track and recognize human activities.
A) Terrestrial Entities
Humans :
Vehicles:
B) Marine Entities
Boats surveillance can be achieved in visible spectrum or IR spectrum . The idea is to count, to track and to recognize boats in fluvial canals, in river, or in open sea.
C) Aerial Entities
Airport visual surveillance mainly concerns the area where aircrafts are parked and maintained by specialized ground vehicles such as fueling vehicles and baggage cars as well as tracking of individuals such as workers. The need of visual surveillance is given due to the following reasons: (1) an airports apron is a security relevant area, (2) it helps to improve transit time, i.e. the time the aircraft is parking on the apron, and (3) it helps to minimize costs for the company operating the airport, as personal can be deployed more efficiently,and to minimize latencies for the passengers, as the time needed for accomplishing ground services decreases.
Reference:
B. Garcia-Garcia, T. Bouwmans, A. Rosales-Silva, "Background Subtraction in Real Applications: Challenges, Current Models and Future Directions", Computer Science Review, Volume 35, February 2020.
CDnet 2014 Dataset
CDnet 2014 Dataset
AGVS Dataset