Pedestrian detection based on a hybrid Gaussian model and support vector machine. Issue 10 (3rd October 2022)

• Record Type: Journal Article
• Authors: Du, Feng; Wang, Wan-Liang; Zhang, Zhi
• Is Part Of: Enterprise information systems. Volume 16:Issue 10/11(2022)
• Page Start: 1515
• Page End: 1526
• Publication Date: 2022-10-03
• Subjects: Pedestrian detection -- hybrid Gaussian model -- region extraction -- histogram of gradient direction -- support vector machine; Information storage and retrieval systems -- Periodicals; Management information systems -- Periodicals; Electronic commerce -- Periodicals; 658.4038011
• DOI: 10.1080/17517575.2020.1791363
• Languages: English
• ISSNs: 1751-7575

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.