Increasing the Robustness of 2D Active Appearance Models for Real-World Applications

Abstract. This paper presents an approach to increase the robustness of Active Appearance Models (AAMs) within the scope of humanrobotinteraction. Due to unknown environments with changing illumination conditions and different users, which may perform unpredictable head movements, standard AAMs suffer from a lack of robustness. Therefore, this paper introduces several methods to increase the robustness of AAMs. In detail, we optimize the shape model to certain applications by using genetic algorithms. Furthermore, a modified retinex-filter to reduce the influence of illumination is presented. These approaches are finally combined with an adaptive parameter fitting approach, which can handle bad initializations. We obtain very promising results of experiments evaluating the IMM face database [1]. Key words: Active Appearance Model, Genetic Algorithm, Retinexfilter, Illumination, Optimization

• Type: Conference
• Year: 2009
• Where: ICVS
• Authors: Ronny Stricker, Christian Martin, Horst-Michael Gross
• Keywords: Active Appearance Model, Computer Vision, Genetic Algorithm, ICVS 2009, Unpredictable Head Movements