Robust Active Appearance Models Search Algorithm

With the aid of AAMs search algorithm, Active Appearance Models (AAMs) can represent non-rigid image objects with shape and texture variations well. However, the performance of the traditional AAMs search algorithm(TAAMS) is limited by its assumption that the error function is convex. Therefore, this paper proposes a robust AAMs search algorithm (RAAMS) which combines the multi-pose search (MS) for better pose matching and an estimation mechanism of parameter search direction (EPSD) for more accurate search direction. Moreover, a precaution mechanism of local minimum (PLM) is proposed to avoid the search trapped into the local minimum of the error function. Experimental results show that the proposed algorithm can significantly reduce 36.41% of shape error and 30.81% of texture error between the synthesized instance and target image.