The development and testing of Thai facial soft tissue thickness data in three-dimensional computerized forensic facial reconstruction.
Аннотация
Forensic facial reconstruction is a useful tool to assist the public in recognizing human remains, leading to positive forensic investigation outcomes. To reproduce a virtual face, facial soft tissue thickness is one of the major guidelines to reach the accuracy and reliability for three-dimensional computerized facial reconstruction, a method that is making a significant contribution to improving forensic investigation and identification. This study aimed to develop a facial soft tissue thickness dataset for a Thai population, and test its reliability in the context of facial reconstruction. Three-dimensional facial reconstruction was conducted on four skulls (2 males and 2 females, with ages ranging between 51 to 60 years). Two main tools of three-dimensional computer animation and modeling software-Blender and Autodesk Maya-were used to rebuild the three-dimensional virtual face. The three-dimensional coordinate (x, y, z) cutaneous landmarks on the mesh templates were aligned homologous to the facial soft tissue thickness markers on the three-dimensional skull model. The final three-dimensional virtual face was compared to the target frontal photograph using face pool comparison. Four three-dimensional virtual faces were matched at low to moderate levels, ranging from 30% to 70% accuracy. These results demonstrate that the facial soft tissue thickness database of a Thai population applied in this study could be useful for three-dimensional computerized facial reconstruction purposes.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.