FaceScope: Advancing Face Detection Systems for Enhanced Security and Interaction

Abstract

Several applications ranging from security and surveillance to human- computer interaction, face detection is an essential part of computer vision. In order to attain high accuracy and real-time processing capabilities, this research provides a thorough examination of face detection technologies using a combination of classical and deep learning-based methodologies. The project starts with an Introduction of the history and development of face detection systems, emphasizing the technology's importance in a range of practical uses. The research is driven by the growing need for reliable and effective face detection systems in many contexts. The problem statement highlights the difficulties encountered in practical face detection settings and delineates the project's goals. In order to address the significance of face identification in real-world circumstances, the project seeks to create a system with high accuracy, adaptability to changing ambient conditions, and real-time processing capabilities._x000D_ An Introduction of face detection algorithms is given in the methodology section, along with information on the approaches and techniques chosen for the project. Preprocessing procedures, feature extraction methods, and classifier selection are all included in this, with an emphasis on striking a compromise between efficiency and accuracy. The project's resilience and flexibility are facilitated by its utilization of both conventional and deep learning-based methodologies.