期刊文献+

基于单目视觉的行人检测研究 被引量:4

Algorithm for Pedestrian Detection Based on Monocular Vision
下载PDF
导出
摘要 行人检测系统是目前先进驾驶辅助系统中直接面向行人的保护系统,可最大程度地减少行人所受到的伤害。纹理对称度特征是目前最直观且能够用于表征行人的特征。文中在采用基于纹理对称度特征方法提取感兴趣区域的基础上,提出了一种线检测的方法,可以有效地减少检测过程中阴影、树叶等小纹理对检测结果的影响。最后利用梯度方向直方图特征和支持向量机方法对感兴趣区域进行验证。试验结果表明,该方法在保证检测速度的前提下,可减少检测过程中的虚警和漏警情况。 Pedestrian detection system is the pedestrian protection system in advanced driving-assistant system, which can effectively reduce pedestrian injury. Texture symmetry degree is currently the most proper feature that can describe pedestrians. A linear detection method is proposed by extracting the region of interest based on texture symmetry degree to effectively reduce the influence of small textures, such as shadow and leaves. The regions of interest are verified by histogram features of gradient direction and support vector machine method. Experiments show that the proposed method can significantly reduce false alarms and missing alarm without affecting the detecting speed.
出处 《电子科技》 2014年第8期22-25,共4页 Electronic Science and Technology
关键词 行人检测系统 对称度特征 线检测 支持向量机 pedestrian detection system symmetry feature line detection support vector machine
  • 相关文献

参考文献9

  • 1贾慧星,章毓晋.车辆辅助驾驶系统中基于计算机视觉的行人检测研究综述[J].自动化学报,2007,33(1):84-90. 被引量:69
  • 2BROGGI A, BERTOZZI M, CHAPUIS R, et al. Shape - based pedestrian detection [ C ]. Proceedings of the IEEE Intelligent Vehicles Symosium ,2000:328 - 333.
  • 3BERTOZZI M, BROGGI A. Infrared stereo vision- based pe- destrian detection [ J]. Intelligent Vehicles Sy,nposium Pro- ceedings IEEE ,2005 ( 6 ) :24 - 29.
  • 4COLLADO J M, HILARAO C, ESCALERA A L,et al. Model based vehicle detection for intelligent vehicles [ C]. Procs. IEEE Intelligent Vehicles Symposium,2004 572 -577.
  • 5NAVNEET D, BILL T. Histograms of oriented gradients fnr human detection [ C ]. Proceedings of the 2005 IEEE Com- puter Society Conference on Computer Vision and Pattern Recognition ,2005 ( 15 ) :886 - 893.
  • 6CORINNA C. Vladimir vpanik.support - vector networks [ J ]. Machine Learing, 1995 ( 20 ) :273 - 297.
  • 7DAVID GEROO' NIMO, ANTONIO M,LOO' PEZ. Survey of pedestrian detection for advanced driver assistance systems [J]. IEEE Transactions on Pattern Analysis And Machine Inteligence, 2010,32 ( 7 ) : 1239 - 1258.
  • 8郑瀚,韦文斌,齐子城.机器视觉检测胶囊图像的预处理研究[J].电子科技,2012,25(12):133-136. 被引量:4
  • 9衡浩,熊惠霖.复杂动态场景下基于道路平面提取的行人检测[J].计算机仿真,2013,30(9):161-164. 被引量:2

二级参考文献55

  • 1阮秋琦.数字图像处理[M].2版.北京;电子工业出版社,2007.
  • 2Gavrila D M, Giebel J, Munder S. Vision-based pedestrian detection: the protector system. In: Proceedings of IEEE Intelligent Vehicles Symposium. Parma, Italy. IEEE, 2004. 13-18
  • 3Tons M, Doerfler R, Meinecke M M, Obojski M A. Radar sensors arid sensor platform used for pedestrian protection in the EC-funded project SAVE-U. In: Proceedings of IEEE Intelligent Vehicles Symposium. Parma, Italy. IEEE, 2004. 813-818
  • 4Broggi A, Bertozzi M, Fascioli A, Sechi M. Shape-based pedestrian detection. In: Proceedings of IEEE Intelligent Vehicles Symposium. Dearborn, USA. IEEE, 2000. 215-220
  • 5Shashua A, Gdalyahu Y, Hayun G. Pedestrian detection for driving assistance systems: single-frame classification and system level performance. In: Proceedings of IEEE Intelligent Vehicles Symposium. Parma, Italy. IEEE, 2004. 1-6
  • 6Xu Feng-Liang, Liu Xia, Fujimura K. Pedestrian detection and tracking with night vision. IEEE Transactions on Intelligent Transportation Systems, 2005, 6(1): 63-71
  • 7Zhao Liang, Thorpe C. Stereo and neural network-based pedestrian detection. IEEE Transactions on Intelligent Transportation Systems, 2000, 1(3): 148-154
  • 8Oren M, Papageorgiou C, Sinha P, Osuna E, Poggio T.Pedestrian detection using wavelet templates. In: Proceed-ings of IEEE Conference on Computer Vision and Pattern Recognition. San Juan, Puerto Rico. IEEE, 1997. 193-199
  • 9Mohan A, Papageorgiou C, Poggio T. Example-based object detection in images by components. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(4):349-361
  • 10Cheng Hong, Zheng Nan-Ning, Qin Jun-Jie. Pedestrian detection using sparse Gabor filter and support vector machine. In: Proceedings of IEEE Intelligent Vehicles Sympo-sium. Vienna, Austria. IEEE, 2005. 583-587

共引文献72

同被引文献33

引证文献4

二级引证文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部