A Vehicle Detection Algorithm Based on Deep Belief Network

Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these ap...

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Main Authors: Hai Wang, Yingfeng Cai, Long Chen
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/647380
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author Hai Wang
Yingfeng Cai
Long Chen
author_facet Hai Wang
Yingfeng Cai
Long Chen
author_sort Hai Wang
collection DOAJ
description Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN) is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets.
format Article
id doaj-art-97273bcdc7954fb9a0503c64bdcf1e76
institution Kabale University
issn 2356-6140
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language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-97273bcdc7954fb9a0503c64bdcf1e762025-02-03T01:28:51ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/647380647380A Vehicle Detection Algorithm Based on Deep Belief NetworkHai Wang0Yingfeng Cai1Long Chen2School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, ChinaAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, ChinaVision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN) is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets.http://dx.doi.org/10.1155/2014/647380
spellingShingle Hai Wang
Yingfeng Cai
Long Chen
A Vehicle Detection Algorithm Based on Deep Belief Network
The Scientific World Journal
title A Vehicle Detection Algorithm Based on Deep Belief Network
title_full A Vehicle Detection Algorithm Based on Deep Belief Network
title_fullStr A Vehicle Detection Algorithm Based on Deep Belief Network
title_full_unstemmed A Vehicle Detection Algorithm Based on Deep Belief Network
title_short A Vehicle Detection Algorithm Based on Deep Belief Network
title_sort vehicle detection algorithm based on deep belief network
url http://dx.doi.org/10.1155/2014/647380
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AT yingfengcai avehicledetectionalgorithmbasedondeepbeliefnetwork
AT longchen avehicledetectionalgorithmbasedondeepbeliefnetwork
AT haiwang vehicledetectionalgorithmbasedondeepbeliefnetwork
AT yingfengcai vehicledetectionalgorithmbasedondeepbeliefnetwork
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