One-Shot Face Recognition

Facial recognition is one of the most fascinating and interesting research areas. It has attracted the attention of many scientists and researchers for its amazing applications in identity authentication, policing, healthcare, marketing, and security. There are different face recognition algorithms available that give very good results but at the cost of huge data. Humans can recognize a person just by seeing a person once but this is not the case for computers they need enormous amounts of data just to recognize a person. In the case of a small dataset, only one algorithm stands out which is one-shot learning. In the case of ‘‘One-shot’’ learning, the model learns from a single input image. The thought is to train a CNN model with an enormous dataset of individuals with different faces, expressions, and lighting conditions specified model once given a single image of an individual will be recognized properly. For this, we tend to use the ‘‘Siamese neural network’’ to be told the similarity between faces.