Research And Implementation Of Face Detection Method Based On Video Image

With the progress of human society, the artificial intelligence is developed quickly, and face detection technology for its friendly and great prospect as its outstanding representative is to become the research focus in this area. How to quickly and efficiently detect and identify the face recognition algorithm is a known goal. Adaboost algorithm for face detection algorithm is very popular and identification of areas of learning algorithms. Compared with other algorithms, Adaboost algorithm in real-time fast, stable and has a good generalization ability, their ability to have a good solution in dealing with the phenomenon of over-learning problems and difficulties of high dimensionality, the performance has obvious advantages, thus highly respected researchers in recent years, increasing the researchers also made significant progress.To achieve this goal, this paper uses the method of theoretical and empirical research, describes the relevant technical and theoretical face detection, etc., and to develop the study of face detection technology and methods of research and detection system, based on how to design and implement Adaboost algorithm face detection system were discussed and explored. In addition, the paper analyzes the characteristics of face detection methods, and discusses the key technologies such as VC ++ 6.0 platform, OpenCV software, combined with face detection system feasibility analysis of the design, in-depth analysis of the application requirements Detection System, including functional requirements and performance requirements of the system modules. On this basis, the paper also outlines the design of the system and the system was discussed, which outline the overall process design, including architecture and system design, and detailed design of the system is the human face detection system and its various functional modules in detail the design.In addition, this article in OpenCV software, MFC with VC ++ 6.0 development platform development environment for C ++ language function Adboost algorithm based face detection system and its various functional modules, then the detection system for functional and performance testing, direction and value of the Adaboost algorithm and other algorithms compare the advantages and disadvantages, so clearly Adaboost algorithm based face detection system development and design, has a certain reference and research significance.