This study addresses the problem of efficiently combining the joint, RGB and depth
modalities of the Kinect sensor in order to recognise human actions. For this purpose, a multi …

Video analytics is the practice of combining digital video data with machine learning models
to infer various characteristics from that video. This capability has been used for years to …

With the uptake of intelligent data-driven applications, edge computing infrastructures
necessitate a new generation of admission control algorithms to maximize system …

In video surveillance, different security spots are considered to be placed in unconstrained
locations. Cameras located on corridors, gateways and roads, have raised the need for new …

Nowadays, video cameras have become a necessary part of everyday life. These cameras
can be found at various places for surveillance, health care, emergencies and disasters. In …

Executing video analytics tasks using a large camera network is a challenging problem in
the field of video processing. Video compression is a necessary step to reduce video data …

Terrorists see transit and passenger rail as an attractive target. Designed for public
convenience, trains and stations offer terrorists easy access to crowds of people in confined …

Object detection is the most important stage due to its great impact on next stages. Moving
objects detections in real environment have several challenges such as dynamic …

Videoanalytiikkaa voidaan hyödyntää muun muassa automatisoimaan väkivaltaisuuden
tunnistamista videovalvontakameroista ja näin parantaa kaupunkiturvallisuutta …

Location and time are critical to the success of many organizations' missions. Sensors,
software, processors, vehicles, and human analysts work together to accomplish these tasks …