基于描述符辅助光流跟踪匹配的数据关联方法

夏华佳; 章红平; 陈德忠; 李团

基于描述符辅助光流跟踪匹配的数据关联方法

武汉大学卫星导航定位技术研究中心武汉 430079

基金项目:

国家重点研发计划项目（SQ2018YFE020091）、长江勘测规划设计研究院开放创新基金项目（CX2020K04）资助

详细信息

作者简介:
夏华佳(1996-),硕士研究生.研究方向:视觉/INS组合导航.E-mail:67010973@qq.com

通讯作者:
章红平(1977-),博士,教授.研究方向:GNSS/INS组合导航.E-mail:hpzhang@whu.edu.cn

中图分类号: V249.32+8
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出版历程
- 收稿日期: 2021-11-06
- 网络出版日期: 2021-12-14

Data Association Method Based on Descriptor Assisted Optical flow Tracking Matching

GNSS Research Center, Wuhan University, Wuhan Hubei 430079, China

摘要

摘要: 针对采用多状态约束卡尔曼滤波（MSCKF）的视觉惯性里程计定位精度易受特征点匹配异常值影响问题，提出了一种基于描述符辅助光流跟踪匹配的数据关联方法。该方法采用金字塔LK光流对序列图像中特征点进行跟踪匹配，计算每一对匹配点的rBRIEF描述符，根据Hamming距离对描述符的相似度进行判断消除异常匹配点。在实验中从特征点匹配主观效果以及定位精度两个方面评估本文方法的有效性。结果表明：所提出方法能够有效滤除动态场景下图像特征匹配的异常值，使用该方法处理后的图像进行MSCKF运动解算，位置结果漂移率小于0.38%，相较于未剔除异常匹配值的MSCKF算法结果，改善了54.7%，单帧图像处理时间约为39 ms。
- 视觉惯性 /
- 数据关联方法 /
- 特征点匹配 /
- rBRIEF描述符 /
- 光流跟踪 /
- MSCKF
Abstract: in the view of the problem that the positioning accuracy of visual inertial odometer using multi-state constrained Kalman filter(MSCKF) is easily affected by the abnormal value of feature point matching, a data association method based on descriptor assisted optical flow tracking matching is proposed. This method uses pyramid LK optical flow to track and match the feature points in the sequence image, then calculates the rbrief descriptor of each pair of matching points, judges the similarity of the descriptor according to the Hamming distance,and eliminates the abnormal matching points. In the experiment, the effectiveness of the proposed method is evaluated from two aspects:the subjective effect of feature point matching and positioning accuracy. The results show that the proposed method can effectively filter the abnormal values of image feature matching in dynamic scene. The image processed by this method is used for msckf motion solution,and the drift rate of position result is less than 0.38%, compared with the result of msckf algorithm without eliminating abnormal matching values,The improvement is 54.7%, and the single frame image processing time is about 39 ms.
- visual inertial /
- data association method /
- feature matching /
- rbrief descriptor /
- optical flow tracking /
- MSCKF

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参考文献(17)

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