Semi-Automatic Identification Photo Generation with Facial Pose and Illumination Normalization

Identification photo is a category of facial image that has strict requirements on image quality like size, illumination, user expression, dressing, etc. Traditionally, these photos are taken in professional studios. With the rapid popularity of mobile devices, how to conveniently take identification photo at any time and anywhere with such devices is an interesting problem. In this paper, we propose a novel semi-automatic identification photo generation approach. Given a user image, facial pose and expression are first normalized to meet the basic requirements. To correct uneven lighting condition in photo, an facial illumination normalization approach is adopted to further improve the image quality. Finally, foreground user is extracted and re-targeted to a specific photo size. Besides, background can also be changed as required. Preliminary experimental results show that the proposed method is efficient and effective in identification photo generation compared to commercial software based manual tunning.