An Improved Pedestrian Detection Algorithm Integrating Haar-Like Features and HOG Descriptors | Zendy

Yun Wei | Zendy; Qing Tian | Zendy; Teng Guo | Zendy

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An Improved Pedestrian Detection Algorithm Integrating Haar-Like Features and HOG Descriptors

Author(s) -

Yun Wei,

Qing Tian,

Teng Guo

Publication year - 2013

Publication title -

advances in mechanical engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.318

H-Index - 40

eISSN - 1687-8140

pISSN - 1687-8132

DOI - 10.1155/2013/546206

Subject(s) - pedestrian detection , haar like features , support vector machine , pedestrian , artificial intelligence , adaboost , computer science , haar , histogram , pattern recognition (psychology) , histogram of oriented gradients , machine learning , engineering , face detection , image (mathematics) , facial recognition system , transport engineering , wavelet

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

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