Monitoring of Video Surveillance

• Published in: International journal for research in applied science and engineering technology 2023-04, Vol.11 (4), p.983-988
• Main Authors: Ponnapalli, Bharath, Kutukuppala, Gangadhara Sai, Monavarthi, Sandeep, Goli, Sri Vachan, Rajesh, B.
• Format: Article
• Language: English
• ISSN: 2321-9653; 2321-9653
• DOI: 10.22214/ijraset.2023.50212

The system gathers a sizable dataset of human faces during the data gathering phase in order to train the machine learning algorithms. In the face detection phase, computer vision algorithms are used to discover and recognise human faces in an image or video stream. You may accomplish this by using The deep convolutional neural network (CNN) architecture of the VGG16 algorithm is one of the most widely used algorithms for this job. The VGG16 algorithm has produced cutting-edge outcomes in a variety of computer vision applications, such as face recognition. Computer vision and machine learning algorithms that can detect and validate human faces. Access control, monitoring, and security systems are just a few examples of the many uses for the system. Data gathering, face detection, face recognition, and verification are a few of the processes that the project goes through. A personal identification method called face recognition analyzes a person's physical features to determine their identity to detect and extract facial features from the Image. The process for recognizing faces in humans consists of two phases: face detection, which occurs quickly in people unless the face is nearby, and introduction, which identifies faces as belonging to specific people