计算机科学 ›› 2017, Vol. 44 ›› Issue (Z11): 175-177.doi: 10.11896/j.issn.1002-137X.2017.11A.036

• 模式识别与图像处理 • 上一篇    下一篇

航拍视频中运动目标检测算法研究

唐佳林,郑杰锋,李熙莹,苏秉华   

  1. 北京理工大学珠海学院信息学院 珠海519088,北京理工大学珠海学院信息学院 珠海519088,中山大学工学院智能交通研究中心 广州510006;广东省智能交通系统重点实验室 广州510006,北京理工大学珠海学院信息学院 珠海519088
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受广东省科技计划项目(2013B051000044),广东大学生科技创新培育专项资金(pdjh2017b0927),广东省青年创新人才项目(2016KQNCX204)资助

Research on Detecting Algorithm of Moving Target in Aerial Video

TANG Jia-lin, ZHENG Jie-feng, LI Xi-ying and SU Bing-hua   

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对复杂背景下航拍视频中的运动目标检测问题,提出一种基于改进的特征匹配算法与全局运动补偿的防抖方法,以及结合多帧能量累积的运动目标检测算法。首先,采取局部区域匹配法加快该算法的处理速度,避免运动目标对背景补偿的影响;其次,利用尺度不变的SURF算法,结合快速近似最邻近搜索算法得到匹配点对,并通过双向匹配和K-近邻算法筛选优秀匹配点;然后,建立仿射变换模型,求解运动参数,并进行运动补偿;最后,通过多帧能量累积进行目标检测。仿真结果表明,该方法具有良好的运动目标检测效果。

关键词: 航拍视频,特征匹配,快速近似最邻近搜索算法,运动补偿,运动目标检测

Abstract: A detecting algorithm of moving target based on the combination between multiple frame energy accumulation and a stabilization method which is combined between improved feature matching algorithm and global motion compensation according to the moving target detection in the aerial video under complex background was proposed.Firstly,it uses the matching method of local area to increase the processing speed of the algorithm,and avoids the influence of the moving target on the background compensation.Secondly,it gets the matching points using the scale-invariant SURF algorithm in combination with the fast approximate nearest neighbor search method,and screens the superior matching points with bilateral matching and k-nearest Neighbor algorithm.Thirdly,it builds the affine transformation model,solves the motion parameters,and makes motion compensation.Finally,it detects moving target through multiple frame difference accumulation.The simulation results show that the method has good effect on moving target detection.

Key words: Aerial video,Feature matching,Fast approximate nearest neighbor search algorithm,Motion compensation,Moving target detection

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