Real-time vehicle detection and tracking in video based on faster R-CNN

Content Provider	Scilit
Author	Zhang, Yongjie Wang, Jian Yang, Xin
Copyright Year	2017
Description	Journal: Journal of Physics: Conference Series Vehicle detection and tracking is a significant part in auxiliary vehicle driving system. Using the traditional detection method based on image information has encountered enormous difficulties, especially in complex background. To solve this problem, a detection method based on deep learning, Faster R-CNN, which has very high detection accuracy and flexibility, is introduced. An algorithm of target tracking with the combination of Camshift and Kalman filter is proposed for vehicle tracking. The computation time of Faster R-CNN cannot achieve realtime detection. We use multi-thread technique to detect and track vehicle by parallel computation for real-time application.
Related Links	http://iopscience.iop.org/article/10.1088/1742-6596/887/1/012068/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/887/1/012068
Journal	Journal of Physics: Conference Series
Issue Number	1
Volume Number	887
Language	English
Publisher	IOP Publishing
Publisher Date	2017-08-01
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Hardware and Architecture Detection Method Vehicle Detection and Tracking Faster R Cnn
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy