Abstract: This study proposes a new method of extracting and tracking a non_rigid object moving while allowing a static camera. For object extraction we first detect an object using a spiking neural networks for extracting its edge. For object tracking we take this edge as model of the object to localize and match its motion in the next frame by using a Hausdorff distance. The model of object is then updated at each frame along the video sequence. The parameters used are adjusted efficiently along the trajectory of the target to ensure a best track.