Tracking Multiple Moving Objects Using Unscented Kalman Filtering Techniques

Understand

It is an important task to reliably detect and track multiple moving objects for video surveillance and monitoring.

• However, when occlusion occurs in nonlinear motion scenarios, many existing methods often fail to continuously track multiple moving objects of interest.
• In this paper we propose an effective approach for detection and tracking of multiple moving objects with occlusion.
• Moving targets are initially detected using a simple yet efficient block matching technique, providing rough location information for multiple object tracking.