Segmentation and tracking of static and moving objects in video surveillance scenarios
Jaime Gallego, Montse Pardàs, Jose-Luis Landabaso · 2008
In this paper we present a real-time object tracking system for monocular video sequences with static camera. The workflow is based on a pixel-based foreground detection system followed by foreground object tracking. The foreground detection method performs the segmentation in three levels: Moving Foreground, Static Foreground and Background level. The tracking uses the foreground segmentation for identifying the tracked objects, but minimizes the reliance on the foreground segmentation, using a modified Mean Shift tracking algorithm. Combining this tracking system with the Multi-Level foreground segmentation, we have improved the tracking results using the classification in static or moving objects. The system solves successfully a high percentage of the moving objects occlusions, and most of the occlusions between static and moving objects.