测绘通报 ›› 2023, Vol. 0 ›› Issue (5): 101-106,163.doi: 10.13474/j.cnki.11-2246.2023.0144

• 学术研究 • 上一篇    下一篇

桥梁自然特征点的快速精确跟踪算法

何雨薇, 诸葛盛, 徐祥鹏, 钟立军, 杨夏, 张小虎   

  1. 中山大学航空航天学院, 广东 深圳 518107
  • 收稿日期:2022-07-06 发布日期:2023-05-31
  • 通讯作者: 张小虎。E-mail:zhangxiaohu@mail.sysu.edu.cn
  • 作者简介:何雨薇(1998-),女,硕士生,主要研究方向为无人机集群协同对大型建筑视觉测量与基于视觉的无人机自定位方法。E-mail:1079965771@qq.com
  • 基金资助:
    国家自然科学基金(U1734208)

Fast and accurate tracking algorithm for natural feature points of bridge

HE Yuwei, ZHUGE Sheng, XU Xiangpeng, ZHONG Lijun, YANG Xia, ZHANG Xiaohu   

  1. College of Aeronautics and Astronautics, Sun Yat-Sen University, Shenzhen 518107, China
  • Received:2022-07-06 Published:2023-05-31

摘要: 特征点跟踪作为无人机对桥梁挠度进行视觉测量的关键技术,跟踪算法的速度和精度直接影响测量的实时性和有效性。本文首先通过加速稳健特征(SURF)匹配得到图像序列特征点的初步定位结果,然后使用相位相关法对特征点进行精确配准,并提出了一种基于无人机运动连续性的加速策略,用于桥梁自然特征点跟踪。利用无人机采集的4 K桥梁视频数据对本文算法进行测试,结果表明,本文算法对于桥梁自然特征点能够实现稳定跟踪,跟踪速度为25 FPS,跟踪精度达到亚像素级别,满足测量要求,能够为视觉测量提供技术支撑。

关键词: 自然特征点跟踪, 视觉测量, 精确配准, 无人机运动连续性, 加速策略

Abstract: Feature point tracking is the critical technique of visual measurement of bridge deflection by UAV, the speed and precision of the tracking algorithm will directly affect the efficiency and accuracy of the measurement. In this paper, the initial location results of the feature points in the image sequence are obtained through surf feature matching, and then the feature points are accurately registered using the phase correlation method. An acceleration strategy based on the motion continuity of UAV is proposed to track the natural feature points of the bridge. The performance of the presented approach is verified through an image sequence of the bridge captured by a UAV, and the results of the experiment show that the average speed of the proposed algorithm is 25 FPS, and the tracking accuracy is sub-pixel level, which meets the measurement requirements, and provides technical support for visual measurement.

Key words: natural feature point tracking, visual measurement, precise registration, UAV motion continuity, acceleration strategy

中图分类号: