Clustering Consumer Photos Based on Face Recognition

Abstract

The main aim of this thesis was to detect the face in an image and its recognition using Python programming language along with OpenCV computer vision library. The practical framework of this research was mainly focused on face detection and recognition. The Haar Cascade algorithm was used for face detection purposes. For facial recognition, the Local Binary Pattern Histogram Algorithm was used. The rapid growth of artificial intelligence and machine learning technology in today's generation has taken the world to the next level. Furthermore, many impossible circumstances that are challenged by human beings can be solved with the aid of the latest technologies such as artificial intelligence and machine learning. Artificial intelligence and machine learning have wide applications in different fields. For example, computer vision, robotics, medical treatment, gaming, and industries. Data is essential for machine learning and artificial intelligence as well as in many projects. To understand artificial intelligence simply, it helps to unlock any devices like smartphones that recognize the face. Furthermore, the thesis explains the development trend of artificial intelligence as well as machine learning and the area of applications. Therefore, the thesis is a complete package of theoretical knowledge along with the practical implementation of artificial intelligence and machine learning application.