• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A reliable quasi-dense corresponding points for structure from motion


Abstract

A three-dimensional (3D) reconstruction is an important research area in computer vision. The ability to detect and match features across multiple views of a scene is a critical initial step. The tracking matrix W obtained from a 3D reconstruction can be applied to structure from motion (SFM) algorithms for 3D modeling. We often fail to generate an acceptable number of features when processing face or medical images because such images typically contain large homogeneous regions with minimal variation in intensity. In this study, we seek to locate sufficient matching points not only in general images but also in face and medical images, where it is difficult to determine the feature points. The algorithm is implemented on an adaptive threshold value, a scale invariant feature transform (SIFT), affine SIFT, speeded up robust features (SURF), and affine SURF. By applying the algorithm to face and general images and studying the geometric errors, we can achieve quasi-dense matching points that satisfy well-functioning geometric constraints. We also demonstrate a 3D reconstruction with a respectable performance by applying a column space fitting algorithm, which is an SFM algorithm.


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Cite this article

[IEEE Style]
J. Oh, H. Hong, Y. Cho, H. Yun, K. Seo, H. Kim, M. Kim and O. Lee, "A reliable quasi-dense corresponding points for structure from motion," KSII Transactions on Internet and Information Systems, vol. 14, no. 9, pp. 3782-3796, 2020. DOI: 10.3837/tiis.2020.09.012.

[ACM Style]
Jangseok Oh, Hyunggil Hong, Yongjun Cho, Haeyong Yun, Kap-Ho Seo, Hochul Kim, Mingi Kim, and Onseok Lee. 2020. A reliable quasi-dense corresponding points for structure from motion. KSII Transactions on Internet and Information Systems, 14, 9, (2020), 3782-3796. DOI: 10.3837/tiis.2020.09.012.

[BibTeX Style]
@article{tiis:23861, title="A reliable quasi-dense corresponding points for structure from motion", author="Jangseok Oh and Hyunggil Hong and Yongjun Cho and Haeyong Yun and Kap-Ho Seo and Hochul Kim and Mingi Kim and Onseok Lee and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2020.09.012}, volume={14}, number={9}, year="2020", month={September}, pages={3782-3796}}