Abstract: Pedestrian detection method has a wide range of application in intelligent monitoring system, intelligent assistant driving, human-computer interaction and so on. Aiming at the problems of traditional classifier based on AdaBoost and SVM, this paper uses AdaBoost and rbfsvm algorithm to design classifier for pedestrian detection, and uses opencv in feature extraction. Finally, through the experimental analysis, the results show that the AdaBoost rbfsvm cascade classifier designed in this paper is superior to the traditional AdaBoost cascade classifier in terms of classification accuracy and false alarm rate, and can also ensure the training speed and detection speed of the classifier.

Key words: AdaBoost, rbfsvm, hog, opencv