Fast and Accurate Digital Morphometry of Facial Expressions

Abstract

Facial surgery deals with a part of the human body that is of particular importance in everyday social interactions. The perception of a person's natural, emotional, and social appearance is significantly influenced by one's expression. This is why facial dynamics has been increasingly studied by both artists and scholars since the mid-Renaissance. Currently, facial dynamics and their importance in the perception of a patient's identity play a fundamental role in planning facial surgery. Assistance is needed for patient information and communication, and documentation and evaluation of the treatment as well as during the surgical procedure. Here, the quantitative assessment of morphological features has been facilitated by the emergence of diverse digital imaging modalities in the last decades. Unfortunately, the manual data preparation usually needed for further quantitative analysis of the digitized head models (surface registration, landmark annotation) is time-consuming, and thus inhibits its use for treatment planning and communication. In this article, we refer to historical studies on facial dynamics, briefly present related work from the field of facial surgery, and draw implications for further developments in this context. A prototypical stereophotogrammetric system for high-quality assessment of patient-specific 3D dynamic morphology is described. An individual statistical model of several facial expressions is computed, and possibilities to address a broad range of clinical questions in facial surgery are demonstrated.

A facial reconstruction method based on new mesh deformation techniques

“…Soft tissue depth tables are usually used in combination with a large database of face templates [ 4 ]. Facial templates can be acquired by non-invasive techniques such as stereophotogrammetry [ 9 ], making the constitution of a large database painless and easy. However, despite the acquisition of dense surface templates for describing the outer face, the average values of soft tissue thickness are systematically measured on a sparse set (<53) of (manually positioned) anatomical landmarks.…”