一种稳健性增强和精度提升的增量式运动恢复结构方法

doi:10.11947/j.AGCS.2019.20170665

测绘学报 ›› 2019, Vol. 48 ›› Issue (2): 207-215.doi: 10.11947/j.AGCS.2019.20170665

一种稳健性增强和精度提升的增量式运动恢复结构方法

于英^1,3,4, 张永生¹, 薛武^2,3,4, 王涛¹

1. 信息工程大学地理空间信息学院, 河南郑州 450001;
2. 航天工程大学, 北京 101416;
3. 地理信息工程国家重点实验室, 陕西西安 710054;
4. 城市空间信息工程北京市重点实验室, 北京 100000

收稿日期:2017-11-24 修回日期:2018-06-21 出版日期:2019-02-20 发布日期:2019-03-02
作者简介:于英(1985-),男,博士,研究方向为无人机摄影测量。E-mail:yuying5559104@163.com
基金资助:
国家自然科学基金（41501482）；地理信息工程国家重点实验室开放研究基金（SKLGIE2015-M-3-6）；城市空间信息工程北京市重点实验室经费（2017203）

A incremental structure from motion method of robustness enhancement and accuracy improvement

YU Ying^1,3,4, ZHANG Yongsheng¹, XUE Wu^2,3,4, WANG Tao¹

1. Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China;
2. Space Engineering University, Beijing 101416, China;
3. State Key Laboratory of Geo-information Engineering, Xi'an 710054, China;
4. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100000, China

Received:2017-11-24 Revised:2018-06-21 Online:2019-02-20 Published:2019-03-02
Supported by:
The National Natural Science Foundation of China(No. 41501482);The Fund of State Key Laboratory of Geo-information Engineering(No. SKLGIE 2015-M-3-6);The Fund of Beijing Key Laboratory of Urban Spatial Information Engineering(No. 2017203)

摘要/Abstract

摘要：

增量式运动恢复结构（ISFM）实现了无序影像的三维重建，在精细化建模、现实场景三维记录以及互联网影像三维重建等领域发挥了重要的作用。但增量式运动恢复结构方法仍存在稳健性差和精度低等方面的问题，常导致三维重建结果难以令人满意甚至三维重建失败，严重限制了增量式运动恢复结构技术的发展应用。本文提出了一种增强稳健性、提升精度的运动恢复结构方法。本文方法有如下3点贡献：①针对立体影像特征匹配结果误差点多的问题，提出了一种顾及特征响应值的参数自适应RANSAC方法，在有效剔除误匹配的同时，最大限度地保留了正确的匹配点；②设计了一种顾忌稳健性和重建精度的下一张影像添加策略，使得重建的过程更加合理；③将外点剔除引入到平差优化过程中，提高平差的稳健性和精度。分别采用无人机低空影像数据、近景拍摄数据以及利用互联网搜索引擎下载的大尺度影像数据进行了试验，结果表明，本文方法可稳健剔除误匹配点、优化影像重建顺序和减弱误差点对平差结果的影响。

关键词: 增量式运动恢复结构, RANSAC, 评分策略, 误匹配点剔除

Abstract:

The Incremental structure from motion(ISFM) method realizes 3D reconstruction based on unordered images and plays an important role in fields such as fine modeling, 3D recording of realistic scenes and 3D reconstruction of Internet images. When facing with the complexity of the scene structure, the ISFM method has some problems, such as poor robustness and low accuracy, which often leads to unsatisfactory 3D reconstruction results and even failure of 3D reconstruction, which severely limits its development and application. An incremental structure from motion method of robustness enhancement and accuracy improvement is constucted. The main improvements are:① Facing the problem that there are many error points in stereo image feature matching, a parameter adaptive RANSAC method which takes into account the feature response value is proposed, which can effectively remove the mismatch and keep the correct matching point to the maximum extent. ② A strategy of adding the next image to avoid robustness and reconstruction accuracy is proposed, which makes the process of reconstruction more reasonable. ③ The elimination of outer points into the adjustment process is introduced, which significantly improves the robustness and accuracy of the adjustment. Finally, by using UAV low-altitude image data, close-range shooting data and Internet-downloaded image data respectively, the experimental results show that this method can effectively eliminate the mismatch points, optimize the image reconstruction sequence and weaken the effect of error points on the adjustment results.

Key words: incremental structure from motion, RANSAC, scoring strategy, error elimination

中图分类号:

P231

于英, 张永生, 薛武, 王涛. 一种稳健性增强和精度提升的增量式运动恢复结构方法[J]. 测绘学报, 2019, 48(2): 207-215.

YU Ying, ZHANG Yongsheng, XUE Wu, WANG Tao. A incremental structure from motion method of robustness enhancement and accuracy improvement[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(2): 207-215.

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一种稳健性增强和精度提升的增量式运动恢复结构方法

A incremental structure from motion method of robustness enhancement and accuracy improvement

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