Methodological Insights Towards Leveraging Performance in Video Object Tracking and Detection

Video Object Detection and Tracking (VODT), one of its integral operations of surveillance system in present time, mechanizes a way to identify and track the target object autonomously and seamlessly within its visual field. However, the challenges associated with video feeding are immensely high, and the scene context is out of human control, posing an impediment to a successful model of VODT. The presented work has discussed about effectiveness of existing VODT approaches considering its identified taxonomies viz. satellite based, remote sensing-based, unmanned-based, Real-time Tracking based, behavioral analysis and event detection based, integration of multiple data sources, and privacy and ethics. Further, research trend associated with cumulative publications and evolving methods to realize the frequently used methodologies in VODT. Further, the results of review showcase that there is prominent research gap of manifold attributes that demands to be addressed for improving performance of VODT.