Pedestrian detection algorithm combining HOG and SLBP

被引：0
作者：
Wang A. [1 ]
Wang M. [1 ]
Zhang J. [1 ]
Iwahori Y. [2 ]
Wang B. [1 ]
机构：
[1] Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin
[2] Dept. of Computer Science, Chubu University
来源：
| 1600年 / Science and Engineering Research Support Society卷 / 11期
关键词：
HIKSVM; HOG; Pedestrian detection; SLBP;
D O I：
10.14257/ijmue.2016.11.10.17
中图分类号：
学科分类号：
摘要：
In order to solve the problem of pedestrian detection performance, the described operator was improved. In this paper, semantic local binary pattern (SLBP) and histogram of oriented gradient (HOG) are combined as new feature operator. This feature method would enrich the information and enhance the detection performance. And then histogram intersection kernel support vector machine (HIKSVM) classifier is trained by the augment feature. Because the time cost is too large by the conventional SVM. HIKSVM could make up this drawback, and significantly reduce the training time. The experiments on the INRIA pedestrian dataset show that the method obtained significant improvement in accuracy comparing to HOG descriptors. © 2016 SERSC.
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收藏
页码：175 / 182
页数：7
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