Verifying the Facial Kinship Evidence to Assist Forensic Investigation Based on Deep Neural Networks

The criminal incident evidence can be considered as the substance of the search for the crime perpetrator. Even if the offender received the deserved punishment. However, when the requisite time for catching the culprit was shorter, the society’s confidence of security and justice will be higher. Thus, justice agencies should custom any new technology which contributes to this process as soon as possible. Kinship Verification can be regarded an interesting and difficult area of study in computer vision and computing forensics. Facial Kinship Verification has the capability to predicts whether two people are related in kinship or not depending on the facial images or videos. Facial Kinship Verification has a diversity of real-world practices, including forensic investigations, contributing to the resolution of missing person cases, social media analysis, and genealogy research. The proposed approach involves the Verification of the relationship which exists between the provided facial images using a Three-Dimensional Convolution Neural Network. This approach involves of following stages: face preprocessing, deep features extraction and Classification. Extensive experiments revealed promising results compared with many state-of-the-art approaches. The accuracy of proposed system reached to 89.25% in KinFaceW-I dataset.