Volume 8 Number 1 (Jan. 2013)
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JSW 2013 Vol.8(1): 71-77 ISSN: 1796-217X
doi: 10.4304/jsw.8.1.71-77

Cascade Classifier Using Combination of Histograms of Oriented Gradients for Rapid Pedestrian Detection

Wenhui Li1, Yifeng Lin1, Bo Fu1, Mingyu Su1, Wenting Wu2
1College of Computer Science and Technology, Jilin University, Changchun 130012, China
2CSR Qishuyan Locomotive & Rolling Stock Technology Reaching Institute co., Ltd, Changzhou 213011, China

Abstract—Accurate and efficient human detection has become an important area for research in computer vision. In order to solve problems in the past human detection algorithms such as features with fixed sizes, fixed positions and fixed number, the human detection based on united Hogs algorithm was proposed. This algorithm can dynamically generate the features closer to human body contours. Basically maintaining the detection speed, the detection accuracy was improved by our algorithm. We demonstrate that comparing with human detection algorithm using haar, traditional hogs and a hog with variable-size blocks, our algorithm is better in both of detection rate and false positive rate.

Index Terms—Pedestrian detection, hog, adaboost, weak classifier, cascade classifier.

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Cite: Wenhui Li, Yifeng Lin, Bo Fu, Mingyu Su, Wenting Wu, "Cascade Classifier Using Combination of Histograms of Oriented Gradients for Rapid Pedestrian Detection," Journal of Software vol. 8, no. 1, pp. 71-77, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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