Volume 39 Issue 6
Dec.  2021
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XIA Huajia, ZHANG Hongping, CHEN Dezhong, LI Tuan. A Data Association Method Based on Tracking and Matching of Assisted Optical Flows from the Descriptor[J]. Journal of Transport Information and Safety, 2021, 39(6): 153-161. doi: 10.3963/j.jssn.1674-4861.2021.06.018
Citation: XIA Huajia, ZHANG Hongping, CHEN Dezhong, LI Tuan. A Data Association Method Based on Tracking and Matching of Assisted Optical Flows from the Descriptor[J]. Journal of Transport Information and Safety, 2021, 39(6): 153-161. doi: 10.3963/j.jssn.1674-4861.2021.06.018

A Data Association Method Based on Tracking and Matching of Assisted Optical Flows from the Descriptor

doi: 10.3963/j.jssn.1674-4861.2021.06.018
  • Received Date: 2021-07-06
    Available Online: 2022-01-12
  • The positioning accuracy of visual inertial odometer using multi-state constrained Kalman filter(MSCKF)is easily affected by mismatching points. A data association method is proposed for mitigating these outliers in this study. First, pyramid Lucas-Kanade(LK)optical flow is used to track and match the features among the sequence images. Second, the rBRIEF descriptors of each pair of matching points are achieved. Third, the Hamming distances between two rBRIEF descriptors can be calculated. Furthermore, the similarity of these descriptors is then evaluated according to Hamming distance. Last, the matching points of low similarity are eliminated as outliers in the data processing. The performances of the proposed method is assessed by the effectiveness of matching and positioning accuracy of the feature point. The results indicate that the proposed method can eliminate mismatching points in dynamic image processing. The outlier-eliminated images are applied for the MSCKF motion estimation. The derived drift rate of positioning result is less than 0.38% and shows an improvement of 54.7% with no outlier-eliminated MSCKF algorithm. The single-frame image processing time is about 39 ms.

     

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