基于计算机视觉的舰船模型三维重建方法

3D reconstruction method for ship models based on computer vision

为保证舰船模型三维重建的完整性以及细节程度,提出基于计算机视觉的舰船模型三维重建方法。基于双目立体视觉计算全局舰船目标点云坐标,生成舰船全局的三维点云数据;多视角点云配准方法对该数据进行配准后,输入多尺度特征递归卷积的稠密点云重建网络模型中,通过该模型生成舰船模型三维深度图,在此基础上,利用运动结构法完成舰船深度图中的三维曲线重建,对舰船模型进行颜色渲染,输出舰船模型三维重建结果。测试结果显示,该方法能够完成不同图像之间对应点的可靠匹配,确定各点的坐标位置;三维重建后模型的空间偏差均在0.015以下;能够较好地完成舰船结构的重建,重建后舰船模型的完整性较好,清晰呈现舰船的结构细节。

To ensure the integrity and level of detail of ship model 3D reconstruction,a computer vision based ship model 3D reconstruction method is proposed.This method is based on binocular stereo vision to calculate the coordinates of the global ship target point cloud and generate three-dimensional point cloud data of the ship as a whole;After registering the data using a multi view point cloud registration method,it is input into a dense point cloud reconstruction network model using multi-scale feature recursive convolution.Through this model,a deep 3D depth map of the ship model is generated.Based on this,the motion structure method is used to reconstruct the 3D curve in the ship depth map,render the color of the ship model,and output the 3D reconstruction result of the ship model.The test results show that this method can achieve reliable matching of corresponding points between different images and determine the coordinate positions of each point;The spatial deviation of the model after 3D reconstruction is all below 0.015;The reconstruction of the ship structure can be completed well,and the integrity of the reconstructed ship model is good,presenting the structural details of the ship clearly.