NDLI: Fast pedestrian detection method based on BING

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Fast pedestrian detection method based on BING

Content Provider	IET Digital Library
Author	Zhao, Yong Cui, Zhongwei Zhang, Yongjun Xu, Wenbo Liang, Hao Zuo, Yu
Abstract	Pedestrian detection is one of hot topics in the field of computer vision and pattern recognition, which is of great value to video surveillance, intelligent traffic and human-computer interaction, etc. and how to improve detection rate and speed is the key. Most traditional pedestrian detection methods are based on the pyramid sliding window scanning method, and for images in which the majority of the region does not contain a body, the detection is inefficient. This study presents a body window sampling algorithm based on binarised normed gradients, which can quickly and effectively extract the window of the image that most likely contains human body to be identified, thus greatly improving the detection speed and obtaining a lower false alarm rate. The authors employ the histogram of oriented gradient feature and the linear support vector machine to train the classifier. For the same false test case in comparison with the pyramid scanning method, when the authors used 2,000 sampling windows for detection, they observed a detection rate increase of 11%, the detection speed increased 19.6 times. For 5,000 sampling windows, the detection rate increased by 20% and the detection speed increased 7.8 times.
Starting Page	653
Ending Page	658
Page Count	6
Volume Number	2020
e-ISSN	20513305
Issue Number	Issue 13, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2020/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.1160
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2020-01-31
Access Restriction	Open
Rights License	Creative Commons Attribution-Non Commercial-No Derivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Subject Keyword	2000 Sampling Windows 5000 Sampling Windows Body Window Computer Vision Computer Vision And Image Processing Technique Detection Rate Increase Detection Speed Fast Pedestrian Detection Method Feature Extraction Great Application Value Human Body Human-computer Interaction Image Classification Image Recognition Important Bottleneck Intelligent Monitoring Intelligent Tourism Intelligent Transportation Knowledge Engineering Technique Learning in AI Object Detection Optical, Image And Video Signal Processing Pedestrian Pyramid Scanning Method Road Safety Statistics Support Vector Machine Window Scanning Method
Content Type	Text
Resource Type	Article

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