Face and Eye tracking system

Abstract

Advancements in computer vision and machine learning have given rise to the development of sophisticated face and eye tracking systems, which have profoundly transformed human-computer interaction and biometric applications. This research paper seeks to delve into the state-of-the-art techniques, challenges, and applications of these systems. By precisely detecting and tracking facial features and eye movements, these systems enable a diverse range of applications, including gaze estimation, attention analysis, emotion recognition, and biometric identification. The paper offers an overview of the underlying technologies, algorithms, and methodologies employed in face and eye tracking systems, while emphasizing their significance in various domains, such as gaming, advertising, healthcare, and security. Additionally, the paper explores the challenges encountered in creating robust and real-time tracking systems, encompassing issues like variations in lighting conditions, occlusions, and user-specific characteristics. The research aims to illuminate the potential of face and eye tracking systems in enhancing user experiences, bolstering biometric security, and catalyzing the development of innovative applications in the continually evolving field of computer vision.