People Identification from the CCTV Footage

Abstract

This study integrates cutting-edge face detection, deblurring, and similarity evalua- tion technologies to build an integrated system of facial recognition. In the paper this novel GFP-GAN, face deblurring, reveals the very good quality of facial images’ sharp- ening. Besides it is a Siamese network that is used to investigate facial dissimilarity, this library also delivers perfect results in distinct facial feature extraction. This advanced method has developed a solution that is going to be used in different areas such as human- machine interaction, security and surveillance. Besides that, combining this sophisticated technology also makes facial analysis more advanced and improves the level accuracy and dependability in many cases. Through Siamese network, MTCNN, and GFP-GAN inte- gration, the project has exhibited its commitment to the growth of autonomous systems based face revelation for general applications like human-computer interaction, security and surveillance. This increased level of coverage enables a comprehensive software solu- tion for such real-world applications. The merging of these modern technologies creates the situations that are suitable for the facial analysis system to be both modern and reliable in all those cases.The bulk of the project implementation was shown using the Siamese network, MTCNN, and GFP-GAN integration which are proof of its purpose- fulness. This built-in framework covers all protruding facial image processing operations and offers the perfect solution for applications in areas like human-computer interaction, security and surveillance. Assimilating these advanced technologies not only boosts the overall level facial analysis but it also creates materials for the improved accuracy and reliability in different events. The Siamese network, MTCNN, and GFP-GAN integration really present the project’s strong commitment to media which may advance the accurate processing of natural facial images for advanced applications in the real world.