Real-time hierarchical facial performance capture
Luming Ma, Zhigang Deng · 2019
This paper presents a novel method to reconstruct high resolution facial geometry and appearance in real-time by capturing an individual-specific face model with fine-scale details, based on monocular RGB video input. Specifically, after reconstructing the coarse facial model from the input video, we subsequently refine it using shape-from-shading techniques, where illumination, albedo texture, and displacements are recovered by minimizing the difference between the synthesized face and the input RGB video. In order to recover wrinkle level details, we build a hierarchical face pyramid through adaptive subdivisions and progressive refinements of the mesh from a coarse level to a fine level. We both quantitatively and qualitatively evaluate our method through many experiments on various inputs. We demonstrate that our approach can produce results close to off-line methods and better than previous real-time methods.