MVE: a multi-view reconstruction environment

ABSTRACT

We present MVE, the Multi-View Environment. MVE is an end-to-end multi-view geometry reconstruction software which takes photos of a scene as input and produces a surface triangle mesh as result. The system covers a structure-from-motion algorithm, multi-view stereo reconstruction, generation of extremely dense point clouds, and reconstruction of surfaces from point clouds. In contrast to most image-based geometry reconstruction approaches, our system is focused on reconstruction of multi-scale scenes, an important aspect in many areas such as cultural heritage. It allows to reconstruct large datasets containing some detailed regions with much higher resolution than the rest of the scene. Our system provides a graphical user interface for structure-from-motion reconstruction, visual inspection of images, depth maps, and rendering of scenes and meshes.

References

1. {AZB94} Armstrong M., Zisserman A., Beardsley P. A.: Euclidean Reconstruction from Uncalibrated Images. In British Machine Vision Conference (BMVC) (1994), pp. 509--518. 2
2. {BETVG08} Bay H., Ess A., Tuytelaars T., Van Gool L.: Speeded-Up Robust Features (SURF). Computer Vision and Image Understanding (CVIU) 110, 3 (June 2008), 346--359. 2
3. {CL96} Curless B., Levoy M.: A Volumetric Method for Building Complex Models from Range Images. In Proceedings of ACM SIGGRAPH (1996), pp. 303--312. 3
4. {FCSS10} Furukawa Y., Curless B., Seitz S. M., Szeliski R.: Towards Internet-scale Multi-view Stereo. In Conference on Computer Vision and Pattern Recognition (CVPR) (2010). 3
5. {FG11} Fuhrmann S., Goesele M.: Fusion of Depth Maps with Multiple Scales. In Proceedings of ACM SIGGRAPH Asia (2011), pp. 148: 1--148: 8. 2, 3, 4
6. {FG14} Fuhrmann S., Goesele M.: Floating Scale Surface Reconstruction. In Proceedings of ACM SIGGRAPH (2014). 2, 3, 4, 5, 6
7. {FP10} Furukawa Y., Ponce J.: Accurate, Dense, and Robust Multi-View Stereopsis. Transactions on Pattern Analysis and Machine Intelligence (PAMI) 32, 8 (2010), 1362--1376. 2, 3
8. {GSC^*07} Goesele M., Snavely N., Curless B., Hoppe H., Seitz S.: Multi-View Stereo for Community Photo Collections. In International Conference on Computer Vision (ICCV) (Oct 2007), pp. 1--8. 3, 6
9. {KBC12} Kolev K., Brox T., Cremers D.: Fast Joint Estimation of Silhouettes and Dense 3D Geometry from Multiple Images. Transactions on Pattern Analysis and Machine Intelligence (PAMI) 34, 3 (2012), 493--505. 3
10. {KH13} Kazhdan M., Hoppe H.: Screened Poisson Surface Reconstruction. ACM Transactions on Graphics 32, 3 (2013), 29: 1--29: 13. 2, 4
11. {KKDH07} Kazhdan M., Klein A., Dalal K., Hoppe H.: Unconstrained Isosurface Extraction on Arbitrary Octrees. In Eurographics Symposium on Geometry Processing (SGP) (2007). 4
12. {LF95} Luong Q.-T., Faugeras O.: The Fundamental matrix: theory, algorithms, and stability analysis. International Journal of Computer Vision (IJCV) 17 (1995), 43--75. 2
13. {Low04} Lowe D. G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision (IJCV) 60, 2 (Nov. 2004), 91--110. 2
14. {MKG11} Mücke P., Klowsky R., Goesele M.: Surface Reconstruction from Multi-Resolution Sample Points. In Vision, Modelling and Visualization (VMV) (2011). 2
15. {PGV^*03} Pollefeys M., Gool L. V., Vergauwen M., Cornelis K., Verbiest F., Tops J.: 3D Recording for Archaeological Field Work. Computer Graphics and Applications (CGA) 23, 3 (2003), 20--27. 2
16. {PKG98} Pollefeys M., Koch R., Gool L. V.: Self-Calibration and Metric Reconstruction in spite of Varying and Unknown Internal Camera Parameters. In International Conference on Computer Vision (ICCV) (1998), pp. 90--95. 2
17. {SCD^*06} Seitz S., Curless B., Diebel J., Scharstein D., Szeliski R.: A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms. In Conference on Computer Vision and Pattern Recognition (CVPR) (2006). 3
18. {SSS06} Snavely N., Seitz S. M., Szeliski R.: Photo Tourism: Exploring Photo Collections in 3D. ACM Transactions on Graphics 25, 3 (2006), 835--846. 2, 3
19. {Sze10} Szeliski R.: Computer Vision: Algorithms and Applications. Springer, 2010. 2
20. {VLPK12} Vu H.-H., Labatut P., Pons J.-P., Keriven R.: High Accuracy and Visibility-Consistent Dense Multiview Stereo. Transactions on Pattern Analysis and Machine Intelligence (PAMI) 34, 5 (2012), 889--901. 3
21. {WMG14} Waechter M., Moehrle N., Goesele M.: Let there be color! --- Large-scale texturing of 3D reconstructions. In Proceedings of the European Conference on Computer Vision (2014). 7
22. {Wu13} Wu C.: Towards Linear-Time Incremental Structure from Motion. In International Conference on 3D Vision (3DV) (June 2013), pp. 127--134. 2, 3

Index Terms

• Computing methodologies

  • Computer graphics

    • Shape modeling

• Theory of computation

  • Randomness, geometry and discrete structures