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A Rapid Method Based on Vehicle Video for Multiobjects Detection
Joint Authors
Wei, Yun
Zhang, Long
Fei, Wei-wei
Zhao, Wen-hua
Tian, Qing
Source
Advances in Mechanical Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-25
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
An efficient and rapid method for car detection in video is presented in this paper.
In this method, rear side view of cars is used in the detection phase.
And in combination with histograms of oriented gradients (HOG) which is one of the most discriminative features, a linear support vector machine (SVM) is used for object classification.
Besides, in order to avoid car missing, Kalman filter is used to track the objects.
It is known that the calculation of HOG is complex and costs the most run time.
So the processing time in this method is decreased by using information of objects’ areas from the previous frames.
It is shown by the experimental results that the detection rate can reach 96.20% and is more accurate when choosing the fit interval number such as 5.
It is also illustrated that this method can decrease the calculating time on a large degree when the accuracy is about 94.90% by comparing with traditional method of HOG combining with SVM.
American Psychological Association (APA)
Tian, Qing& Zhang, Long& Wei, Yun& Fei, Wei-wei& Zhao, Wen-hua. 2013. A Rapid Method Based on Vehicle Video for Multiobjects Detection. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-480398
Modern Language Association (MLA)
Tian, Qing…[et al.]. A Rapid Method Based on Vehicle Video for Multiobjects Detection. Advances in Mechanical Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-480398
American Medical Association (AMA)
Tian, Qing& Zhang, Long& Wei, Yun& Fei, Wei-wei& Zhao, Wen-hua. A Rapid Method Based on Vehicle Video for Multiobjects Detection. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-480398
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-480398