Object Tracking by Multiple State Management and Eigenbackground Segmentation

This paper presents a multiple target tracking system through a fixed video camera, based on approaches found in literature. The proposed system is composed of three steps: foreground identification through background subtraction techniques; object association through color, area and centroid position matching, by using the Kalman filter to estimate the object’s position in the next frame; object classification according to an object management system. The obtained results showed that the proposed tracking system was able to recognize and track objects in movement on videos, as well as dealing with occlusions and separations, while encouraging future studies in its application on real time security systems.