Space target three-dimensional sparse reconstruction method based on image sequence trajectory tracking

Abstract

The invention relates to a space target three-dimensional sparse reconstruction method based on image sequence trajectory tracking, and the method comprises the steps: carrying out multi-layer hash image matching through multiple views of a space target, and obtaining a multi-view matching result; carrying out space target multi-view trajectory tracking by utilizing the multi-view matching result;and utilizing a multi-view matching relationship and the multi-view trajectory tracking result to estimate a reconstruction model based on inverse sampling consensus (AC-RANSAC). The established Hamming distance hash table can realize rapid and accurate image matching; after feature tracking, the multi-view effective association number is obtained, so that the stability of stereo matching and theaccuracy of triangulation reconstruction feature point cloud are obviously improved, and the reconstruction number of the feature point cloud is increased; the reverse approach solves the contingencyproblem of the model, whose statistical criteria are data-specific, and avoids empirically setting internal / external differentiated thresholds.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional reconstruction of computer vision, and relates to a three-dimensional sparse reconstruction method of a space target based on image sequence trajectory tracking. Background technique [0002] The 3D sparse reconstruction technology of space targets based on image sequence trajectory tracking is an application of computer vision technology that takes space targets as a new research object, aiming to obtain the 3D model of space targets by collecting image sequences. With the increasing informatization and diversification of space detection, the role of precise monitoring of the space environment is becoming more and more prominent. The development and availability of 3D reconstruction technology for sequence images will make the recognition and matching capabilities from single 2D images to multiple The dimensional hierarchical model is transformed, and the target or scene model database ...

AI Technical Summary

Problems solved by technology

[0004]At present, in the field of 3D sparse reconstruction based on image sequences, there is a lack of targeted and systematic research on space environment targets in China. The research involved is in the early stage of discussion, program analysis, technical demonstration, or some algorithm testing in a limited simulation experiment environment, and a relatively complete theoretical framework has not yet been formed.

In addition, there is no actual measured image as a basis in China at present, and it will face some difficulties that may go beyond the theoretical system of 3D reconstruction. In view of the characteristics of space targets in this project, it is necessary to first solve the non-Lambertian structure of 3D reconstruction (mainly In view of the impact of data damage caused by high light and non-uniform illumination of key space targets, these data damages may bring unpredictable challenges to the robustness of the algorithm. Secondly, satellite targets have thin and linear shapes such as sailboards and antennas. structure, these are major technical problems in the field of 3D reconstruction

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