Abstract
In this paper we present a complete chain of algorithms for detection and tracking of moving objects using a static camera. The system is based on robust difference of images for motion detection. However, the difference of images does not take place directly over the image frames, but over two robust frames which are continuously constructed by temporal median filtering on a set of last grabbed images, which allows working with slow illumination changes. The system also includes a Kalman filter for tracking objects, which is also employed in two ways: assisting to the process of object detection and providing the object state that models its behaviour. These algorithms have given us a more robust method of detection, making possible the handling of occlusions as can be seen in the experimentation made with outdoor traffic scenes.
This work has been supported by the CICYT project COO1999AX014
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Herrero, E., Orrite, C., Alcolea, A., Roy, A., Guerrero, J.J., Sagüés, C. (2003). Video-Sensor for Detection and Tracking of Moving Objects. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_40
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DOI: https://doi.org/10.1007/978-3-540-44871-6_40
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