刘慧, 李清泉, 高春仙, 曾喆. 利用C_SURF配准的空基视频运动目标检测[J]. 武汉大学学报 ( 信息科学版), 2014, 39(8): 951-955. DOI: 10.13203/j.whugis20130121
引用本文: 刘慧, 李清泉, 高春仙, 曾喆. 利用C_SURF配准的空基视频运动目标检测[J]. 武汉大学学报 ( 信息科学版), 2014, 39(8): 951-955. DOI: 10.13203/j.whugis20130121
LIU Hui, LI Qingquan, GAO Chunxian, ZENG Zhe. Moving Target Detection Using C_SURF Registration[J]. Geomatics and Information Science of Wuhan University, 2014, 39(8): 951-955. DOI: 10.13203/j.whugis20130121
Citation: LIU Hui, LI Qingquan, GAO Chunxian, ZENG Zhe. Moving Target Detection Using C_SURF Registration[J]. Geomatics and Information Science of Wuhan University, 2014, 39(8): 951-955. DOI: 10.13203/j.whugis20130121

利用C_SURF配准的空基视频运动目标检测

Moving Target Detection Using C_SURF Registration

  • 摘要: 目的 针对传统的车辆检测算法的性能易受低空移动平台影响造成相机自运动以及外界的干扰等问题,提出了一种基于改进的C_SURF彩色特征稳像和光流法向量相结合的方法来解决低空视频中的运动车辆检测问题。通过图像稳像消除了相机的自运动和外界干扰问题,提高了运动车辆的检测性能。实验结果显示,该方法不仅在检测车辆方面可以获得更好的检测性能,在复杂的背景环境下也能有效地检测运动车辆。

     

    Abstract: Objective Due to the high mobility,rapid deployment and a wide range of monitoring,vehicle detec-tion and tracking system based on low-level mobile platform attract more and more attention.Cameralself-motion,outside interference and other reasons caused by low altitude mobile platforms impact theperformance of traditional vehicle detection algorithms.To resolve the above problems,a new methodon improved SURF color image stabilization is presented in this paper.From the experimental results,we can see,firstly,compared to other methods,the method proposed by the paper can achieve vehicledetection performance;secondly even in a complex background environment,the method in this papercan effectively detect moving vehicles.

     

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