Title: Dense 3D Facial Reconstruction from a Single Depth Image in Unconstrained Environment,
Abstract: With the increasing demands of applications in virtual reality such as 3D
films, virtual Human-Machine Interactions and virtual agents, the analysis of
3D human face analysis is considered to be more and more important as a
fundamental step for those virtual reality tasks. Due to information provided
by an additional dimension, 3D facial reconstruction enables aforementioned
tasks to be achieved with higher accuracy than those based on 2D facial
analysis. The denser the 3D facial model is, the more information it could
provide. However, most existing dense 3D facial reconstruction methods require
complicated processing and high system cost. To this end, this paper presents a
novel method that simplifies the process of dense 3D facial reconstruction by
employing only one frame of depth data obtained with an off-the-shelf RGB-D
sensor. The experiments showed competitive results with real world data.