A Study on End-to-End Face Analysis: How to Cope with Challenges

This paper presents a study on end-to-end implementation of a 2D face analysis project leveraging computer vision technology. Face analysis is a critical application of computer vision that has gained significant attention due to its potential in enhancing security systems, user authentication, and personalized marketing. The study shows some techniques, algorithms, and methodologies employed in face analysis, including using face recognition to recognize celebrities in movies or TV series as well as emotion recognition to recommend music playlists based on facial expressions. To ensure scalability and portability, the paper proposes an effective pipeline to store and retrieve data using specialized data storage file formats. In addition to exploring the intricacies of face analysis technology, this study also addresses the deployment of the developed face analysis system on prominent cloud platforms, such as Google Cloud Platform. It discusses the architecture, configuration, and integration of the system with GCP1.