文献类型：期刊文献

英文题名：Night-time pedestrian detection based on temperature and HOGI feature in infra-red images

作者：Liu, Li[1]; Bao, Hong[1]; Pan, Weiguo[1]; Xu, Cheng[2]

通讯作者：Bao, Hong

机构：[1] Beijing Key Laboratory of Information Service Engineer, Beijing Union University, Beijing, 100101, China; [2] Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

第一机构：北京联合大学北京市信息服务工程重点实验室

年份：2016

卷号：17

期号：28

起止页码：14.1-14.7

外文期刊名：International Journal of Simulation: Systems, Science and Technology

收录：EI(收录号：20164302950453);Scopus(收录号：2-s2.0-84992108828)

语种：英文

外文关键词：Image segmentation - Infrared imaging - Intelligent systems - Object detection

摘要：Pedestrian detection is very important and also has a big challenge in the Intelligent Transportation System. In this paper, our proposed method can detect pedestrians in infrared images robustly. Our method consists of two components. Firstly, the temperature matrix of infrared images is used to extract candidate pedestrians. For it performs robustly under different scenes without delicate parameter tuning. This is different from the traditional threshold or edge based region of interest (ROI) generation techniques. Secondly, the histogram of oriented gradient and intensity (HOGI)feature is extracted from infrared image combining the gradient and intensity feature. Finally, the HOGI features are employed to train classifier based on two kinds of machine learn-ing algorithms. Experimental results in various scenarios demonstrate the robustness and effectiveness of the proposed method. ? 2016, UK Simulation Society. All rights reserved.