<abstract xmlns="http://www.w3.org/1999/xhtml"><p>To reconstruct the points in three dimensional space, we need at least two images. In this paper we compared two different methods: the first uses only two images, the second one uses three. During the research we measured how camera resolution, camera angles and camera distances influence the number of reconstructed points and the dispersion of them. The paper presents that using the two-view method, we can reconstruct significantly more points than using the other one, but the dispersion of points is smaller if we use the three-view method. Taking into consideration the different camera settings, we can say that both the two- and three-view method behaves the same, and the best parameters are also the same for both methods.</p></abstract>

To reconstruct the points in three dimensional space, we need at least two images. In this paper we compared two different methods: the first uses only two images, the second one uses three. During the research we measured how camera resolution, camera angles and camera distances influence the number of reconstructed points and the dispersion of them. The paper presents that using the two-view method, we can reconstruct significantly more points than using the other one, but the dispersion of points is smaller if we use the three-view method. Taking into consideration the different camera settings, we can say that both the two- and three-view method behaves the same, and the best parameters are also the same for both methods.

Comparing two- and three-view computer vision

Sapientia Hungarian University of Transylvania

Acta Universitatis Sapientiae, Informatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Comparing two- and three-view computer vision"}

To reconstruct the points in three dimensional space, we need at least two images. In this paper we compared two different methods: the first uses only two...

Comparing two- and three-view computer vision

Online veröffentlicht: 21. Aug. 2019

Seitenbereich: 41 - 51

Eingereicht: 17. Dez. 2018

DOI: https://doi.org/10.2478/ausi-2019-0003

Schlüsselwörter
computer vision, triangulation, reconstruction

© 2019 Zsolt Levente Kucsván, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Comparing two- and three-view computer vision

Online veröffentlicht: 21. Aug. 2019

Seitenbereich: 41 - 51

Eingereicht: 17. Dez. 2018

DOI: https://doi.org/10.2478/ausi-2019-0003

Schlüsselwörtercomputer vision, triangulation, reconstruction

© 2019 Zsolt Levente Kucsván, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
computer vision, triangulation, reconstruction