Oblique photography three-dimensional reconstruction matching method

Abstract

The invention relates to the field of oblique photography three-dimensional reconstruction of unmanned aerial vehicles, and discloses an oblique photography three-dimensional reconstruction matching method, which comprises the steps of extracting an image position and a pose feature component; extracting an image color feature component; extracting texture feature components; standardizing the three components, and performing combining to obtain a fusion feature vector; constructing a hash function to map the obtained fusion feature vector; and further calculating the Euclidean distance, performing sorting to form a to-be-matched image set, and then selecting a single image matching object from the to-be-matched image set in the structure motion recovery process. Compared with the prior art, POS information and color texture information of an unmanned aerial vehicle image are fused; the images before reconstruction are clustered according to the characteristics of the unmanned aerial vehicle images, the global matching process of a traditional reconstruction algorithm is avoided, the efficiency in oblique photography image three-dimensional reconstruction is remarkably improved, and the reconstruction dense point cloud can keep good precision while the reconstruction efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of three-dimensional reconstruction of oblique photography of unmanned aerial vehicles, in particular to a method for three-dimensional reconstruction and matching of oblique photography. Background technique [0002] In recent years, with the continuous progress and perfection of feature point detection and matching algorithms, self-calibration algorithms, structure from motion reconstruction algorithms (Structure from motion, SFM) and multi-view stereo matching algorithms (Multi-view stereopsis, MVS), Image-based 3D reconstruction technology has developed by leaps and bounds, and has been widely used in forest resource survey, forest stand research and 3D reconstruction of standing trees. Due to the low-altitude flight characteristics of UAVs, it has the advantages of flexible viewing angles and strong timeliness. UAVs can be used to obtain a large number of uncalibrated image sequences of continuous viewi...

AI Technical Summary

Problems solved by technology

Xu Zhihua et al. proposed a method for constructing image topological relationship based on GPS information, which limits the image matching in the process of 3D reconstruction to images with topological relationship ----------------- ---- carried out to reduce the time-consuming matching, but did not consider the situation where the camera position is the same and the shooting angle is completely different

Song Zhengxi et al. divided the image into blocks and constructed an image KD-tree by extracting Sift features before matching. However, the initial image clustering still uses Sift features, and the clustering efficiency is not very high.

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