A robust feature tracker for active surveillance of outdoor scenes

Abstract

In this paper, we propose a robust real-time object detection system for outdoor image sequences acquired by an active camera. The system is able to compensate background changes due to the camera motion and to detect mobile objects in the scene. Background compensation is performed by assuming a simple translation (displacement vector) of the background from the previous to the current frame and by applying the well-known tracker proposed by Lucas and Kanade. A reference map containing all well trackable features is maintained and updated by the system at each frame by introducing new good features related to new regions that appear in the current image. A new method is applied to reject badly tracked features. The current frame and the background after compensation are processed by a change detection method in order to locate mobile objects. Results are presented in the contest of a visual-based surveillance system for monitoring outdoor enviroments.