Facial Trauma Based Real Time Facial Reconstruction Using Machine Learning Algorithm

Facial trauma caused by accidents, injuries, or medical conditions, profoundly affects an individual's quality of life, both physically and psychologically. Medical science has made significant advances in reconstructive surgery to restore the form and function of damaged facial features, the intricate anatomy of the face and the diversity of trauma cases continue to pose challenges for achieving the best possible outcomes. This research aims to enhance the reconstruction of disfigured faces by having resources for advanced face detection techniques by identifying facial landmarks using Histogram of Oriented Gradients (HOG) and calculating the Euclidean distance, thus the system can generate precise suggestions for medical professionals, based on a random forest tree model, a Machine Learning technique, which allows for accurate modeling and adjustment of facial structures.