The development and testing of Thai facial soft tissue thickness data in three-dimensional computerized forensic facial reconstruction

Open-Source 3D Morphing Software for Facial Plastic Surgery and Facial Landmark Detection Research and Open Access Face Data Set Based on Deep Learning (Artificial Intelligence) Generated Synthetic 3D Models

Background: The scarcity of 3D facial models presents a significant hurdle for researchers and educators. Gathering such data demands substantial resources. Objective: To introduce an open-source 3D morphing software to generate 3D facial data sets for research and to provide a large sample data set that is based on synthetically generated 3D models. Methods: Software is developed to morph 3D facial models in bulk by altering landmark locations. Twenty synthetic 3D facial models are generated utilizing deep learning tools and 28 landmarks located on each. The measurements of synthetic models are confirmed to be realistic by comparing them with facial statistics. Several facial deformities and types are simulated at various magnitudes on 3D models to generate a large data set. Results: An open-source software and an open-access data set of 980 3D facial models, each with 28 landmark locations, are provided. Since the data set is based on synthetically generated 3D models, no institutional review board approval is required. Conclusion: The 3D morphing software and the large 3D data set are expected to benefit researchers and educators in the field of facial surgery and facial landmark detection.

Facial reconstruction using 3-D computerized method: A scoping review of Methods, current Status, and future developments

Facial reconstruction (otherwise known as facial approximation) is an alternative method that has been widely accepted in forensic anthropological and archaeological circumstances. This method is considered useful for creating the virtual face of a person based on skull remain. Three-dimensional (3-D) traditional facial reconstruction (known as sculpture or manual method) has been recognized for more than a century; however, it was declared to be subjective and required anthropological training. Until recently, with the progression of computational technologies, many studies attempted to develop a more appropriate method, so-called the 3-D computerized facial reconstruction. This method also relied on anatomical knowledge of the face-skull relationship, divided into semi- and automated based computational method. The 3-D computerized facial reconstruction makes it more rapid, more flexible, and more realistic to generate multiple representations of faces. Moreover, new tools and technology are continuously generating fascinating and sound research as well as encouraging multidisciplinary collaboration. This has led to a paradigm shift in the 3-D computerized facial reconstruction to a new finding and new technique based on artificial intelligence in academia. Based on the last 10-years scientific-published documents, this article aims to explain the overview of the 3-D computerized facial reconstruction and progression as well as an issue relating to future directions to encourage further improvement.