Detection Of Human Faces In Complex Scenes

Human face detection is an important problem in pattern recognition and image processing. And it is the key step of face recognition. With the development of intellectualized technology,human face detection has wide applications in many fields such as security access control,intelligent supervision,video conference and content-based image retrieval. Human faces are familiar to us,but theirs detection is a challenge. If we can find a high-performance solution,it will offer important enlightenment for solving other similar complicated modes'detection problem. It makes studying fast and accurate human face detection technique have important meaning.In this paper, we present an algorithm based on skin segmentation and Support Vector Machines(SVM) to detect frontal views of human faces in sequential color images.We make summaries,comparison,and researches on correlative technologies at the beginning of this paper. This part briefly introduces the concepts of human face detection and SVM,analyzes common face detection methods and how SVM be applied to learning and classifying.The most important part of this paper is the design and realization of human face detection system:we design the system work flow on the basis of system demands,divide it into some sub-modules,and then introduce the design procedure of every module sequentially,finally provide the whole blue print of this system and show the result that system operates at the same time.At last,we carry on comprehensive analysis to the operation result of system and point out the further work.The experiment result shows that the algorithm works efficiently in the complex scenes.