Data processing method and system based on unmanned aerial vehicle video and vector data fusion

Abstract

The present application relates to the technical field of data processing, in particular to a data processing method and system based on unmanned aerial vehicle video and vector data fusion. By calculating the deviation of the predicted position and the actual detection position of each reference point in the image, the reference points with large errors are screened and the camera pose parameters are adjusted using the random consistency algorithm and the iterative optimization method to improve the projection accuracy and stability. Through grid division, corner detection and feature descriptor extraction, a reference point set is established, the parallax change standard deviation is introduced, and the unstable reference points with large fluctuations are removed to ensure the reliability of the pose solving process and the consistency of spatial registration. According to the registration and fusion of unmanned aerial vehicle video and vector geographic data, the problems of current vector element drift, occlusion determination difficulty and attitude error dynamic correction are solved, the spatial reality and dynamic stability of the augmented reality scene are enhanced, and the industrial needs of various application scenarios such as underground pipe network inspection are met.

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