基于单目视觉的高精度三维场景重建技术研究

High Precision 3D Scene Reconstruction Based on Monocular Vision

摘要: 近年来，随着计算机硬件的不断快速更新，计算机的处理能力也不断变强。同时场景三维模型的获取技术越来越成熟，我们获得场景的三维模型数据的方式更多也更加方便了。而目前在基于单目和双目的三维重建技术中，单目技术较双目操作简单、而且取材方面更有利于推向市场。本文主要讲述基于单相机的三维重建，然后通过基于累积图的快速NCC匹配的种子扩张算法来进行高精度的三维场景重建。本章对经典的NCC相似度量函数进行优化，以此减少计算时间。而种子像素扩张算法即先选择初始的种子像素，利用视差图进行窗口比较从而获得高置信度的种子像素，因此大大降低了视差图的误匹配点。试验表明，该方法能够得到高质量的三维场景模型。

Abstract: In recent years, along with the rapid updating of computer hardware, the processing capability of computer is also increasing. At the same time, 3d scene reconstruction technique has become more and more mature and we can get 3d model data for scenarios more easily than ever before. Now, in the 3d reconstruction technology based on monocular and binocular, monocular technology is simpler to operate than binocular technology and more convenient to acquire materials and more favorable to the market. This paper focuses on monocular based 3D reconstruction, the algorithm is used to reconstruct the 3d scene with a fast NCC algorithm based on the cumulative diagram. This paper improves the classic NCC similarity measures to reduce the computation time. Seed pixel expansion algorithm is presented to choose the initial seed pixels, use parallax to make window comparisons to obtain high confidence seed pixels, therefore, the mismatches of the parallax figure are greatly reduced. Experiments show that the method can reconstruct precise and clear 3d scenarios.