期刊文献+

基于视频检测的船舶异常航迹模型及实验分析 被引量:3

下载PDF
导出
摘要 水运交通的发展和桥梁的增多,导致船桥相撞事故的增多,同时现有的船舶交通管理系统及被动防船撞装置在内河通航桥梁防撞上具有一定的局限性,而基于视频监控的主动防船撞预警系统则可以更为有效的进行早期预警。因此本文提出了基于视频检测的桥区内河航道船舶异常航迹模型,分析船舶航速、能见度、运动方向、船队大小、船舶领域、风力、浪高和人为因素等8个指标信息,从而判断船舶航行的异常与否,并实时给出预警信号来避免船撞桥事故的发生。经实验及性能分析,验证了该模型具有较高的准确性,可有效的获取船舶异常航迹,用于主动告警决策。
出处 《江苏船舶》 2012年第4期30-33,共4页 Jiangsu Ship
基金 国家自然基金(60904096) 上海城市建设研究院基金资助项目
  • 相关文献

参考文献5

  • 1ZHANG D, DANIEL G P, BENGIO S, et al. Semi - supervised Adapted HMMs for Unusual Event Detect ion ~ C]// Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition ( CVPR05 )-Volumel-Volume01. Washington: IEEE Com- puter Society, 2005 : 611 - 618.
  • 2LIY, XU C J, LIU J Z. Detecting Irregularity in Videos Using Kernel Estimation and K - D Trees[ C ]//Proceedings of the 14th annual ACM international conterence on Multimedia. New York: ACM Press, 2006 : 639 - 642.
  • 3ZHOU H, K1MBER D. Unusual Event Detection via Multi-camera Video Mining [ C ]//Proceedings of the 18th International Conference on Pattern Recognition Volume 03. Washington: IEEE Computer Society, 2006:1 161-1 166.
  • 4JAIN R. Difference and accumulative difference pictures in dy- namic scene analysis [J]. Image and Vision Computing, 1984, 2(2) : 99 - 108.
  • 5云霄,肖刚.基于Camshift的多特征自适应融合船舶跟踪算法[J].光电工程,2011,38(5):52-58. 被引量:22

二级参考文献9

  • 1曾姝彦,张广军,李秀智.基于Gabor滤波器的图像目标识别方法[J].北京航空航天大学学报,2006,32(8):954-957. 被引量:15
  • 2Dickmanns E D. The development of machine vision for road vehicles in the last decade [C]// IEEE Intemgent Vehicle Symposium, Versailles-France, Jun 17-21, 2002, 1: 268-281.
  • 3Bradski G R. Computer Vision Face Tracking for use in a Perceptual User Interface [J]. lntel Technology Journal(S1535-864X), 1998, 2(2): 1-15.
  • 4COMANICNU D, RAMESH V, MEER P. Real-time tracking of non-rigid objects using Mean Shift [C]//Proceedings of the 2000 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC: IEEE ComputerSociety, 2000: 142-149.
  • 5JAIN R. Difference and accumulative difference pictures in dynamic scene analysis [J]. Image and Vision Computing(S0262-8856), 1984, 2(2): 99-108.
  • 6Health A, Sarkar S, Sanocki T, et al. Comparsion of Edge Detectors: AMethodology and Initial Study [J]. Computer Vision and Image Understanding(S1077-3142), 1998, 69(1): 38-54.
  • 7Haralick R M, Shangmugam K. Texture feature for image classification [J]. IEEE Transactions on System Man and Cybernaties(S0018-9472), 1973, 3(6): 768-780.
  • 8Fashing M, To.masi C. Mean shift is a bound optimization [J]. IEEE Transactions on Pattern Analysis and Machine lntelligence(S0162-S828), 2005, 27(3): 471-474.
  • 9Cheng Y Z. Mean shift, mode seeking, and clustering [J]. IEEE Transactions on Pattem Analysis and Machine Intelligence(S0162-8828), 1995, 17(8): 790-799.

共引文献21

同被引文献9

引证文献3

二级引证文献7

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