用于三维重建的改进特征匹配策略

为了能够更加快速地获取特征点以及提高特征匹配结果的稳定性,提出了一种改进的匹配策略。首先,对图像进行下采样,通过低分辨率的图像进行匹配,快速筛选掉匹配失败的匹配对,然后对匹配成功的匹配对对应的原始图像进行匹配,以达到加速的目的。其次,为有效提高三维点云的精度,对SIFT的匹配结果和SURF的匹配结果进行融合,将融合后的结果应用到三维重建技术中。最后,通过使用自采数据集和公开数据集对算法进行测试,并对实验数据进行分析。结果显示,改进的特征匹配策略使三维重建的运行速度提高了40%,并大幅增加了三维点的个数。所提出的方法不仅可以减少特征匹配过程的运算量,还可以提高三维重建的稳定性,在三维重建研究工作中具有一定的参考价值。

Improved feature matching strategy for 3D reconstruction

In order to get the feature points in the image more quickly and improve the stability of feature matching results, an improved matching strategy is proposed. First, the image is subsampled, matched by a low-resolution image, and the matching pair that matches the failure is quickly filtered out, and then the matched ones that succeed are matched with the corresponding original images, so as to achieve the purpose of acceleration. In addition, the matching result of SIFT and the matching result of SURF are merged, and the fusion result is applied to the 3D reconstruction technology, which effectively improves the accuracy of the 3D point cloud. The algorithm is tested by using self-acquired data set and public data set, and the experimental data is analyzed. The results show that the improved feature matching strategy improves the running speed of 3D reconstruction by 40% and greatly increases the number of 3D points. Therefore, the proposed method can not only reduce the computational burden of feature matching process, but also improve the stability of 3D reconstruction, so it has certain reference value in the research of 3D reconstruction.