Face morphing using critical point filters

Face morphing is an effect that shows a transition from one face image to another face image smoothly. It has been widely used in various fields of work, such as animation, movie production, games, and mobile applications. Two types of methods have been used to conduct face morphing. Semi automatic mapping methods, which allow users to map corresponding pixels between two face images, can produce a smooth transition of result images. Mapping the corresponding pixel between two human face images is usually not trivial. Fully automatic methods have also been proposed for morphing between two images having similar face properties, where the results depend on the similarity of the input face images. In this project, we apply a critical point filter to determine facial features for automatically mapping the correspondence of the input face images. The critical point filters can be used to extract the main features of input face images, including color, position and edge of each facial component in the input images. An energy function is also proposed for mapping the corresponding pixels between pixels of the input face images. The experimental results show that position of each face component plays a more important role than the edge and color of the face. We can summarize that, using the critical point filter, the proposed method to generate face morphing can produce a smooth image transition with our adjusted weight function.