Performance analysis and formative assessment of visual trackers using PETS critical infrastructure surveillance datasets

Abstract

Surveillance of perimeter of critical infrastructures (CIs) has gained a particular attention worldwide due to rising threats of terrorist incidents. However, the generation and dissemination of real-world, challenging datasets concerning CIs for performance assessment of surveillance tasks, particularly tracking, have widely been overlooked in the community. Recent performance evaluation of tracking and surveillance (PETS) workshops have sought to address this issue by introducing ample CI surveillance datasets. We demonstrate the effectiveness of these publicly released real-world PETS CI visual datasets by providing a comprehensive statistically significant performance analysis as well as formative assessment of several state-of-the-art multitarget trackers using well-known and recent performance assessment criteria.