Face Detection Based on Adaboost and Parallel Realization
Bo Song · Jisuanji fangzhen · 2010
Face detection is a fundamental research theme in the topic of Computer Vision,and it has a broad application in many fields such as video surveillance,automatic face recognition,etc.In recent years the face detection algorithm,which based on Adaboost,has been successfully applied because of its rapid speed and acceptable detection rate.However,there are certain blind spots on tilted face detection.On the other hand,the Adaboost learning algorithm has a high computation load and data throughput,as a result,the training process takes a lot of time.To deal with these problems,two new Haar features are proposed in the training process,which have improved the detection effects on tilted human faces.A parallel Adaboost algorithm has also been proposed in this article.It reduces the training time greatly and provides a new path to solve the time consuming problem in the training process.