An Improved Pedestrian Detection Algorithm Integrating Haar-Like Features and HOG Descriptors. (24th November 2013)

• Record Type: Journal Article
• Authors: Wei, Yun; Tian, Qing; Guo, Teng
• Other Names: Wang Wuhong Academic Editor.
• Is Part Of: Advances in mechanical engineering. Volume 2013(2013)
• Publication Date: 2013-11-24
• Subjects: Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1155/2013/546206
• Languages: English
• ISSNs: 1687-8132

Abstract

Abstract : Considering the importance of pedestrian detection in a variety of applications such as advanced robots and intelligent surveillance systems, this paper presents an improved pedestrian detection method through integrating Haar-like features, AdaBoost algorithm, histogram of oriented gradients (HOG) descriptor, and support vector machine (SVM) classifiers, in which the head and shoulder information is utilized especially. Due to the fast training speed of Haar-like features and the high detection efficiency of HOG features, the proposed method can classify pedestrians precisely with higher speed. Experimental results validated the efficiency and effectiveness of the proposed algorithm.