A Novel Approach to Identify Disfigured Faces Using Facial Landmark Detection

In forensic science, identifying damaged faces is a serious difficulty, particularly in circumstances of trauma, decomposition or mass catastrophes. The study aims to design a robust system that helps in the identification and matching of injured faces using reliable facial landmark detection algorithms. The proposed method is to implement state-of-the-art deep learning algorithms to accurately detect and match essential facial landmarks on faces with partial deformity. The comparison of these landmarks to already existing records of the faces helps in quick identification and verification. By utilizing cutting-edge cutting-edge machine learning algorithms, this simplified approach can achieve high accuracy and robustness in forensic identification. The aim is to provide forensic investigators and medical examiners the tools for proper handling of complex identification cases.