Robust 3D face modeling and reconstruction from frontal and side images

Robust and effective capture and reconstruction of 3D face models directly by smartphone users enables many applications. This paper presents a novel 3D face modeling and reconstruction solution that robustly and accurately acquire 3D face models from a couple of images captured by a single smartphone camera. Two selfie photos of a subject taken from the front and side are first used to guide our Non-Negative Matrix Factorization (NMF) induced part-based face model to iteratively reconstruct an initial 3D face of the subject. Then, an iterative detail updating method is applied to the initial generated 3D face to reconstruct facial details through optimizing lighting parameters and local depths. Our iterative 3D face reconstruction method permits fully automatic registration of a part-based face representation to the acquired face data and the detailed 2D/3D features to build a high-quality 3D face model. The NMF part-based face representation learned from a 3D face database facilitates effective global and adaptive local detail data fitting alternatively. Our system is flexible and it allows users to conduct the capture in any uncontrolled environment. We demonstrate the capability of our method by allowing users to capture and reconstruct their 3D faces by themselves.