Real Time Face Recognition Using Convoluted Neural Networks
This is an incremental application for authentication, surveillance, and law enforcement systems.
The paper tackles real-time face recognition by using a Convolutional Neural Network (CNN) model trained on hundreds of images extracted from videos, achieving accurate results for specific persons.
Face Recognition is one of the process of identifying people using their face, it has various applications like authentication systems, surveillance systems and law enforcement. Convolutional Neural Networks are proved to be best for facial recognition. Detecting faces using core-ml api and processing the extracted face through a coreML model, which is trained to recognize specific persons. The creation of dataset is done by converting face videos of the persons to be recognized into Hundreds of images of person, which is further used for training and validation of the model to provide accurate real-time results.