Visual Surveillance Child Missing Alert On Face Based Real World Existence System

In this wide world, identifying a missing child is a challenging problem. Usually, police and CBI write a note on the child's face to catch him if he goes missing or is abducted in a public place. However, due to memory impairment among the general public, it is difficult to get him to remember his face. So, even if they see the child, they do not inform the police and the police consider it a tragedy to catch a child in a public place. In our proposed scheme, automatic identification of children is performed using face recognition from video surveillance. The field of artificial intelligence plays a key role here, identifying the child himself through video surveillance and alerting the police based on the recorded face image. The identification process is carried out through Gaussian feature point extraction, where the facial features of the child are extracted and trained. Based on the trained feature patterns, a recurrent neural network (RNN) is used to classify the child's face among multiple extracted face patterns. If spotted, an email alert is sent to the police using a photo system.