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Journal Article

Citation

Wang H, Cai Y, Chen L. ScientificWorldJournal 2014; 2014: e647380.

Affiliation

Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China.

Copyright

(Copyright © 2014, ScientificWorld, Ltd.)

DOI

10.1155/2014/647380

PMID

24959617

Abstract

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.


Language: en

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