Resolution-Aware 3D Morphable Model

Abstract

The 3D Morphable Model (3DMM) is currently receiving considerable attention for human face analysis.Most existing work focuses on fitting a 3DMM to high resolution images.However, in many applications, fitting a 3DMM to low-resolution images is also important.In this paper, we propose a Resolution-Aware 3DMM (RA-3DMM), which consists of 3 different resolution 3DMMs: High-Resolution 3DMM (HR-3DMM), Medium-Resolution 3DMM (MR-3DMM) and Low-Resolution 3DMM (LR-3DMM).RA-3DMM can automatically select the best model to fit the input images of different resolutions.The multi-resolution model was evaluated in experiments conducted on PIE and XM2VTS databases.The experimental results verified that HR-3DMM achieves the best performance for input image of high resolution, and MR-3DMM and LR-3DMM worked best for medium and low resolution input images, respectively.A model selection strategy incorporated in the RA-3DMM is proposed based on these results.The RA-3DMM model has been applied to pose correction of face images ranging from high to low resolution.The face verification results obtained with the pose-corrected images show considerable performance improvement over the result without pose correction in all resolutions.