Real-time tracking-by-detection framework for traffic applications via deep learning based convolutional neural network
Joint Authors
al-Mustafa, Madah
Yu, Zhu Liang
Source
Issue
Vol. 16, Issue 3 (30 Sep. 2020), pp.381-392, 12 p.
Publisher
Publication Date
2020-09-30
Country of Publication
Algeria
No. of Pages
12
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
Vision-based target tracking is one of the core parts of intelligent traffic video surveillance systems due to its assistance in reducing risks of traffic accidents and traffic jams on roads.
This paper proposes a new tracking-by-detection method in the domain of traffic applications by using the powerful ability of deep learning based object detection technique into vision-based tracking for vehicles.
The proposed method uses transfer learning technique to achieve state-ofthe- art tracking performance but building upon a powerful object detector while only requiring few hundreds of images data for training.
The experimental results not only validates the performance of the proposed transfer learning technique and also shows that tracking can be achieved using this approach.
Furthermore, qualitative and quantitative results on challenging dataset show that the proposed tracking method achieves competitive performance with the state-of-the-art methods.-
American Psychological Association (APA)
al-Mustafa, Madah& Yu, Zhu Liang. 2020. Real-time tracking-by-detection framework for traffic applications via deep learning based convolutional neural network. Journal of Electrical Systems،Vol. 16, no. 3, pp.381-392.
https://search.emarefa.net/detail/BIM-1020898
Modern Language Association (MLA)
al-Mustafa, Madah& Yu, Zhu Liang. Real-time tracking-by-detection framework for traffic applications via deep learning based convolutional neural network. Journal of Electrical Systems Vol. 16, no. 3 (2020), pp.381-392.
https://search.emarefa.net/detail/BIM-1020898
American Medical Association (AMA)
al-Mustafa, Madah& Yu, Zhu Liang. Real-time tracking-by-detection framework for traffic applications via deep learning based convolutional neural network. Journal of Electrical Systems. 2020. Vol. 16, no. 3, pp.381-392.
https://search.emarefa.net/detail/BIM-1020898
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 389-392
Record ID
BIM-1020898