Accurate and Robust 3D Facial Capture Using a Single RGBD Camera

Title: Accurate and Robust 3D Facial Capture Using a Single RGBD Camera

Teams: Microsoft

Writers: Yen-Lin Chen Hsiang-Tao Wu Fuhao Shi Xin Tong Jinxiang Chai

Publication date: December 2013

Abstract

This paper presents an automatic and robust approach that accurately captures high-quality 3D facial performances using a single RGBD camera. The key of our approach is to combine the power of automatic facial feature detection and image-based 3D nonrigid registration techniques for 3D facial reconstruction. In particular, we develop a robust and accurate image-based nonrigid registration algorithm that incrementally deforms a 3D template mesh model to best match observed depth image data and important facial features detected from single RGBD images. The whole process is fully automatic and robust because it is based on single frame facial registration framework. The system is flexible because it does not require any strong 3D facial priors such as blendshape models. We demonstrate the power of our approach by capturing a wide range of 3D facial expressions using a single RGBD camera and achieve state-of-the-art accuracy by comparing against alternative methods.