Three-dimensional reconstruction method for aerial images of unmanned aerial vehicle based on deep learning
A deep learning and three-dimensional reconstruction technology, applied in the field of computer vision, can solve the problems of large amount of calculation, low precision, and difficult to reconstruct dense maps, so as to improve the speed and integrity of reconstruction, reduce the occupation of memory, and achieve high reconstruction accuracy. Effect
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[0054] The invention improves the MVSNet network model so that it can be better applied to the unmanned aerial vehicle carrier. According to the BlendedMVS data set, the improved network model is trained, and the network weight parameters are updated after several iterations to select the optimal network model parameters. Using multiple cameras on the UAV for data collection, which includes uploading the collected aerial image data containing location information in real time, the image sequence is formatted and input to the end-to-end neural network model to obtain the relevant depth map. Using the depth map fusion algorithm technology, the depth map is converted into a 3D point cloud map for storage.
[0055] The present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation steps.
[0056] Such as figure 1 Shown, the concrete implementation method of the present invention is as follows:
[0057] S1. Improve t...
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