A smart pan-tilt-zoom (PTZ) camera is like a robot head that rotates to keep a moving object inside the field of view.

The PTZ camera zooms-in as well, to increase far objects resolution making details more visible for identification and recognition.

PTZ tracking is a very difficult task. The problem is that any algorithm at a certain point will drift. It seems unavoidable. What can be done is detecting the drift, re-initiating the target model and resuming the PTZ tracking.

This can be achieved by a proper detection algorithm that needs to be as fast as possible to prevent the target from escaping the field of view permanently.

Deciding when a drift is happening is crucial as well. Further advancements to the overall tracking algorithms may be investigated.

The project activities will include: study of scientific papers; implementation of detection algorithms on embedded platforms; live test execution with PTZ cameras; performance and computational load evaluation; creation of a tagged video set and implementation of automatic tests on a server.