Combining SfM and ORB Algorithms in 3D Reconstruction
Main Article Content
Abstract
This article presents a new algorithm for 3D reconstruction using a combination of two existing methods – Structure from Motion (SfM) and Oriented FAST and Rotated BRIEF (ORB). The authors propose an approach that merges the advantages of both methods to enhance the accuracy and efficiency of reconstructing the 3D structure of scenes from images. To improve reconstruction quality, filtering and outlier removal are applied, along with other optimizations. Comparative results between the new algorithm and existing methods demonstrate its superiority in accuracy and noise robustness. The proposed approach is highly scalable and can be successfully applied in various fields that require precise 3D reconstruction of image scenes.
Keywords:
Article Details
References
2. Seitz S. M., Dyer C. R. Photorealistic Scene Reconstruction by Voxel Coloring, Proc. Computer Vision and Pattern Recognition Conf. 1997. P. 1067–1073.
3. Fraltsov D. Single image 3D scene reconstruction. toloka.ai [Электронный ресурс]. 2023. URL: https://toloka.ai/blog/3d-scenes-reconstruction
4. Hartley R., Zisserman A. Multiple view geometry in computer vision. Cambridge University press. 2004, 56 p.
5. X. Zhu, H. Hu, S. Lin, J. Dai. Deformable convnets v2: More deformable, better results. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, 16–17 June 2019. P. 9308–9316.
1. Introduction to SURF (Speeded-Up Robust Features). OpenCV documentation [Электронный ресурс]. 2021. URL: https://docs.opencv.org/3.4/df/dd2/tutorial_py_surf_intro.html
7. Seitz S. M. A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms, in Proc. IEEE international Conference on Computer Vision and Pattern Recognition. New York, USA. 2006.
8. Итеративный алгоритм ближайших точек. Wikipedia [Электронный ресурс]. 2021 URL: https://en.wikipedia.org/wiki/Iterative_closest_point
9. Hengyu Y., Hongyang . Incremental SFM 3D reconstruction based on monocular. 13th International Symposium on Computational Intelligence and Design (ISCID). 2020. P. 523.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Presenting an article for publication in the Russian Digital Libraries Journal (RDLJ), the authors automatically give consent to grant a limited license to use the materials of the Kazan (Volga) Federal University (KFU) (of course, only if the article is accepted for publication). This means that KFU has the right to publish an article in the next issue of the journal (on the website or in printed form), as well as to reprint this article in the archives of RDLJ CDs or to include in a particular information system or database, produced by KFU.
All copyrighted materials are placed in RDLJ with the consent of the authors. In the event that any of the authors have objected to its publication of materials on this site, the material can be removed, subject to notification to the Editor in writing.
Documents published in RDLJ are protected by copyright and all rights are reserved by the authors. Authors independently monitor compliance with their rights to reproduce or translate their papers published in the journal. If the material is published in RDLJ, reprinted with permission by another publisher or translated into another language, a reference to the original publication.
By submitting an article for publication in RDLJ, authors should take into account that the publication on the Internet, on the one hand, provide unique opportunities for access to their content, but on the other hand, are a new form of information exchange in the global information society where authors and publishers is not always provided with protection against unauthorized copying or other use of materials protected by copyright.
RDLJ is copyrighted. When using materials from the log must indicate the URL: index.phtml page = elbib / rus / journal?. Any change, addition or editing of the author's text are not allowed. Copying individual fragments of articles from the journal is allowed for distribute, remix, adapt, and build upon article, even commercially, as long as they credit that article for the original creation.
Request for the right to reproduce or use any of the materials published in RDLJ should be addressed to the Editor-in-Chief A.M. Elizarov at the following address: amelizarov@gmail.com.
The publishers of RDLJ is not responsible for the view, set out in the published opinion articles.
We suggest the authors of articles downloaded from this page, sign it and send it to the journal publisher's address by e-mail scan copyright agreements on the transfer of non-exclusive rights to use the work.