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Object tracking in an outdoor environment using fusion of features and cameras
2006
Image and Vision Computing
This paper presents methods for tracking moving objects in an outdoor environment. A robust tracking is achieved using feature fusion and multiple cameras. The proposed method integrates spatial position, shape and color information to track object blobs. The trajectories obtained from individual cameras are incorporated by an extended Kalman filter (EKF) to resolve object occlusion. Our results show that integrating simple features makes the tracking effective and that EKF improves the
doi:10.1016/j.imavis.2005.06.008
fatcat:hpqxeh2kurawxeevfkbc7j2ma4