To promptly and accurately obtain wave surface information,a wave reconstruction process based on binocular stereo vision is established to extract the three-dimensional wave surface distribution from two-dimensional wave surface images.The wave images captured by binocular cameras are used as raw data for camera parameter calibration.Speeded-up robust feature algorithms,pyramid search methods,and epipolar constraints are employed to extract and match wave surface feature points.Finally,the three-dimensional point cloud reconstruction of the wave field is achieved through stereo rectification,disparity map analysis,and post-processing optimization.A uniform grid is created by linear interpolation in the reconstruction area,and the three-dimensional point cloud is projected onto the original two-dimensional wave image for visualization.Research results indicate that under good lighting conditions and relatively high wind and wave levels,the binocular stereo vision model accurately extracts wave surface feature points,and the reconstructed three-dimensional point cloud faithfully represents the wave surface.This approach is convenient to use and has low cost,providing a foundation for subsequent studies on wave level analysis and wave height prediction.
关键词
双目立体视觉/波浪场重构/三维点云/加速鲁棒性特征算法/金字塔搜索法
Key words
binocular stereo vision/wave field reconstruction/three-dimensional point cloud/speeded-up robust feature algorithm/pyramid search method
维普
万方数据