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Robustness and accuracy are major issues in real-time tracking. This paper describes a reliable tracking for markerless planar objects based on the fusion of visual cues and on the estimation of a 2D transformation. Its parameters are estimated by a non-linear minimization of an unique criterion that integrates information on both texture and edges. The efficiency and the robustness of the proposed method are tested on image sequences as well as during a robotic application.