Abstract:A stereo matching algorithm based on deformable convolution is proposed to perform 3D reconstruction of binocular vision.Firstly, the two-dimensional deformable convolution is used to extract the features of the left and right input images.Secondly, the three-dimensional deformable convolution is used to effectively aggregate the relevant features between the two images in the matching cost volume.Finally, a three-stage cascade residual learning method is used to reduce the parameter calculation amount of the matching cost volume, which can meet the real-time requirements of fast matching.According to the principle of the algorithm, the detection of the disparity depth map is completed, and the three-dimensional object is reconstructed through Open3D.The experimental results show that the parameter amount of the algorithm is 0.5×106, the running time is only 0.02s, the generated disparity map has high precision, and the reconstructed 3D effect is good.
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