Person Recognition and Authenticity Through Facial Analysis Combining LSTM and Siamese Networks

The automatic recognition of real people is particularly important in many fields of activity. The article proposes a complex system for recognizing people taking into account possible fraud attacks. A Long Short-Term Memory neural network was used to detect possible frauds in the video sequences, and to recognize the person in the case after validation as a real person, two Siamese neural networks implemented with VGG 16 and ResNet 50 were tested. The obtained results were compared for Euclidean distance, Cosine distance, and for two training methods: Contrastive Loss and Triple Loss. The best results were obtained for VGG 16, Cosine distance, and Triple Loss.