Pedestrian detection based on a hybrid Gaussian model and support vector machine

Abstract

ABSTRACT In order to improve the detection rate of pedestrian, a novel technique that is based on hybrid Gaussian background modeling combined with HOG and SVM is proposed. The random video frame test sample is used to verify the performance of the model. The results show that under the condition of ensuring the detection rate and detection rate, the false detection rate of the hybrid Gauss combined with the HOG + SVM model is only 5.2% in comparison with that of HOG + AdaBoost at 7.1%, which confirms that the model can accurately detect pedestrians in complex scenes in real time.