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A coarse-to-fine approach for vehicles detection from aerial images

  • Long Chen*
  • , Zhiguo Jiang
  • , Junli Yang
  • , Yibing Ma
  • *此作品的通讯作者
  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Vehicles detection in aerial images has a wide range of applications for visual surveillance. This paper introduces a framework for robust on-road vehicle detection. A passively trained framework system is built using conventional supervised learning. The strategy which is proposed for detecting vehicles is From-coarse-to-fine. In the first step, Road is segmented with LSD algorithm to narrow the area which will be detected. AdaBoost based algorithm is used for coarse detection. SVM is used to reduce false rates. Experimental results show that this framework yields a efficient and robust on-board vehicle detection system with high precision and low false rates.

源语言英语
主期刊名Proceedings of International Conference on Computer Vision in Remote Sensing, CVRS 2012
221-225
页数5
DOI
出版状态已出版 - 2012
活动2012 International Conference on Computer Vision in Remote Sensing, CVRS 2012 - Xiamen, 中国
期限: 16 12月 201218 12月 2012

出版系列

姓名Proceedings of International Conference on Computer Vision in Remote Sensing, CVRS 2012

会议

会议2012 International Conference on Computer Vision in Remote Sensing, CVRS 2012
国家/地区中国
Xiamen
时期16/12/1218/12/12

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