Motion segmentation and cloud tracking on noisy infrared image sequences
Résumé
Volume 3653 Aerial surveillance is an issue of key importance for warship protection. In addition to radar systems, infrared surveillance sensors represent an interesting alternative for remote observation. In this paper, we study such a system and an original approach to the tracking of complex cloudy patterns in noisy infrared image sequences is proposed. We have paid particular attention to robustness with regards to perturbations likely to occur (noise, 'lining effects' . . .). Our approach relies on robust parametric motion estimation and an original regularization scheme allows to handle with the appearance and the disappearance of objects in the scene. Numerous experiments performed on outdoor infrared image sequences underline the efficiency of the proposed method.