Developing a Parametric 3D Face Model Editing Algorithm

Min Pang,Ligang He,Xie Han,Liqun Kuang,Zhiying He,Min Chang

doi:10.1109/access.2020.3022987

Min Pang, Ligang He + Show 4 more

Open Access

https://doi.org/10.1109/access.2020.3022987

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Abstract

In the fields of computer graphics and computer vision, a great amount of research and analysis has been conducted on expression-carrying face models. How to construct more realistic and effective 3D face models has become an immense challenge to researchers. This paper proposes a parametric 3D face model editing algorithm based on existing 3D face models. The algorithm takes a number of existing 3D face models with different expressions as input, edits the models through mostly through model deformation and interpolation, and generates a new 3D face model. In particular, the face model editing process begins with selecting multiple face models with different expressions as input. Second, with one of the selected models as the source model and others as the target models, the source model and all target models are registered one by one; meanwhile, the vertex correspondence between the registered models is established. Third, the selected 3D models are parameterized to a planar disc through quasi-conformal mapping. Fourth, relying on the vertex correspondence, a set of corresponding control points between different models are established. The model is then deformed and interpolated under the guidance of the control points and by using the quasi-conformal iteration method, which produces the 2D face models with transitional expressions between the source model and the target models. Finally, the 2D models are restored to the corresponding 3D face models using the model restoration algorithm. Additionally, this paper proposes to use the Beltrami coefficient to guide the quasi-conformal iteration in performing the mapping between two planes. This coefficient then serves as a measure to evaluate the similarity between the edited model and the original one. The proposed algorithm has been evaluated through extensive experiments. The results suggest that compared with existing editing methods, the proposed method is more effective and efficient in constructing various 3D face models.

Highlights

In the human visual perception system, facial expressions take up an important position, because all human emotions are expressed through changes in facial features
In view of the above investigations, this paper proposes a new model editing method, namely a parametric 3D face model editing algorithm based on Iterative Closest Point (ICP) registration
Using the ICP algorithm, the source model and the target models are registered one by one, and they are transferred to the same coordinate system, and the correspondence between their vertices are established in this process

Summary

INTRODUCTION

In the human visual perception system, facial expressions take up an important position, because all human emotions are expressed through changes in facial features. 1) DETERMINING THE CONTROL PARAMETERS OF THE MODEL DEFORMATION PROCESS With the selected 3D human face source model above, its characteristic points can be obtained as described in step 2 of algorithm 1 and saved in set t0 = ti0, i = 1, 2 . K) extracted from the parametric 2D plane of the rest k-1 face models with different facial expressions corresponding to t1, the intermediate point set Tj = Tji, i = 1, 2 . J=2 where i represents the index value of the corresponding characteristic point in the 2D model generated by the quasi-conformal mapping from the selected face model, αij is the weight, used to define the impact of each target model on the generated transition model in the interpolation process, αij.

QUASI-CONFORMAL ITERATION

EXPERIMENTS

CONCLUSION