Abstract
This paper presents a new algorithm aiming for 3D Line Segment (LS) reconstruction in structured scenes that are comprised of a set of planes. Due to location imprecision of image LSs, it often produces many erroneous reconstructions when reconstructing 3D LSs by triangulating corresponding LSs from two images. We propose to solve this problem by first recovering space planes and then back-projecting image LSs onto the recovered space planes to get reliable 3D LSs. Given LS matches identified from two images, we estimate a set of planar homographies and use them to cluster the LS matches into groups such that LS matches in each group are related by the same homography induced by a space plane. In each LS match group, the corresponding space plane can be recovered from the 3D LSs obtained by triangulating all the LS correspondences. To reduce the incidence of incorrect LS match grouping, we formulate to solve the LS match grouping problem into solving a multi-label optimization problem. The advantages of the proposed algorithm over others in this area are that it can generate more complete and detailed 3D models of scenes using much fewer images and can recover the space planes where the reconstructed 3D LSs lie, which is beneficial for upper level applications, like scene understanding and building facade extraction.
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Notes
- 1.
The authors of Line3D++ made the source code of Line3D++ publicly available, but did not do so for its preliminary versions. So, we can only compare our measure data with the reported data in the papers.
References
Agarwal, S., Furukawa, Y., Snavely, N., Simon, I., Curless, B., Seitz, S.M., Szeliski, R.: Building Rome in a day. Commun. ACM 54, 105–112 (2011)
Baillard, C., Schmid, C., Zisserman, A., Fitzgibbon, A.: Automatic line matching and 3D reconstruction of buildings from multiple views. In: ISPRS Conference on Automatic Extraction of GIS Objects from Digital Imagery (1999)
Bartoli, A., Sturm, P.: Structure-from-motion using lines: representation, triangulation, and bundle adjustment. Comput. Vis. Image Underst. 100, 416–441 (2005)
Bay, H., Ess, A., Neubeck, A., Van Gool, L.: 3D from line segments in two poorly-textured, uncalibrated images. In: 3DPVT (2006)
Boykov, Y., Veksler, O., Zabih, R.: Efficient approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell. 36, 1222–1239 (2001)
Chetverikov, D., Svirko, D., Stepanov, D., Krsek, P.: The trimmed iterative closest point algorithm. In: ICPR (2002)
Delmerico, J.A., David, P., Corso, J.J.: Building facade detection, segmentation, and parameter estimation for mobile robot stereo vision. Image Vis. Comput. 31, 841–852 (2013)
Delong, A., Osokin, A., Isack, H.N., Boykov, Y.: Fast approximate energy minimization with label costs. Int. J. Comput. Vis. 96, 1–27 (2012)
Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. IEEE Trans. Pattern Anal. Mach. Intell. 32, 1362–1376 (2010)
Habib, A.F., Morgan, M., Lee, Y.R.: Bundle adjustment with selfcalibration using straight lines. Photogram. Rec. 17, 635–650 (2002)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2003)
Hofer, M., Maurer, M., Bischof, H.: Improving sparse 3D models for man-made environments using line-based 3D reconstruction. In: 3DV (2014)
Hofer, M., Wendel, A., Bischof, H.: Incremental line-based 3D reconstruction using geometric constraints. In: BMVC (2013)
Hofer, M., Maurer, M., Bischof, H.: Efficient 3D scene abstraction using line segments. Comput. Vis. Image Underst. (2016). doi:10.1016/j.cviu.2016.03.017
Li, K., Yao, J., Lu, X., Xia, M., Li, L.: Joint point and line segment matching on wide-baseline stereo images. In: WACV (2016)
Kim, C., Manduchi, R.: Planar structures from line correspondences in a Manhattan World. In: Cremers, D., Reid, I., Saito, H., Yang, M.-H. (eds.) ACCV 2014. LNCS, vol. 9003, pp. 509–524. Springer, Heidelberg (2015). doi:10.1007/978-3-319-16865-4_33
Jain, A., Kurz, C., Thormahlen, T., Seidel, H.P.: Exploiting global connectivity constraints for reconstruction of 3D line segments from images. In: CVPR (2010)
Jensen, R., Dahl, A., Vogiatzis, G., Tola, E.: Large scale multi-view stereopsis evaluation. In: CVPR (2014)
Luong, Q.-T., Viéville, T.: Canonical representations for the geometries of multiple projective views. Comput. Vis. Image Underst. 64, 193–229 (1996)
Matinec, D., Pajdla, T.: Line reconstruction from many perspective images by factorization. In: CVPR (2003)
Micusik, B., Wildenauer, H.: Structure from motion with line segments under relaxed endpoint constraints. In: 3DV (2014)
Micusik, B., Wildenauer, H.: Descriptor free visual indoor localization with line segments. In: 3DV (2015)
Pan, J.: Coherent scene understanding with 3D geometric reasoning. Ph.D. thesis, Carnegie Mellon University (2014)
Pham, T.T., Chin, T.J., Yu, J., Suter, D.: The random cluster model for robust geometric fitting. IEEE Trans. Pattern Anal. Mach. Intell. 36, 1658–1671 (2014)
Přibyl, B., Zemčík, P., Čadík, M.: Camera pose estimation from lines using Plücker coordinates. In: BMVC (2015)
Ramalingam, S., Brand, M.: Lifting 3D Manhattan lines from a single image. In: ICCV (2013)
Schindler, G., Krishnamurthy, P., Dellaert, F.: Line-based structure from motion for urban environments. In: 3DPVT (2006)
Sinha, S.N., Steedly, D., Szeliski, R.: Piecewise planar stereo for image-based rendering. In: ICCV (2009)
Smith, P., Reid, I.D., Davison, A.J.: Real-time monocular SLAM with straight lines. In: BMVC (2006)
Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3D. ACM Trans. Graph. 25, 835–846 (2006)
Snavely, N., Seitz, S.M., Szeliski, R.: Modeling the world from internet photo collections. Int. J. Comput. Vis. 80, 189–210 (2008)
Spetsakis, M.E., Aloimonos, J.Y.: Structure from motion using line correspondences. Int. J. Comput. Vis. 4, 171–183 (1990)
Strecha, C., Hansen, W.V., Gool, L.V., Fua, P., Thoennessen, U.: On benchmarking camera calibration and multi-view stereo for high resolution imagery. In: CVPR (2008)
Taylor, C.J., Kriegman, D.J.: Structure and motion from line segments in multiple images. IEEE Trans. Pattern Anal. Mach. Intell. 17, 1021–1032 (1995)
Teboul, O., Simon, L., Koutsourakis, P., Paragios, N.: Segmentation of building facades using procedural shape priors. In: CVPR (2010)
Werner, T., Zisserman, A.: New techniques for automated architectural reconstruction from photographs. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2351, pp. 541–555. Springer, Heidelberg (2002). doi:10.1007/3-540-47967-8_36
Wu, C.: Towards linear-time incremental structure from motion. In: 3DV (2013)
Zhang, L., Koch, R.: Structure and motion from line correspondences: representation, projection, initialization and sparse bundle adjustment. J. Vis. Commun. Image Represent. 25, 904–915 (2014)
Zhang, Z.: Flexible camera calibration by viewing a plane from unknown orientations. In: ICCV (1999)
Acknowledgment
This work was partially supported by the National Natural Science Foundation of China (Project No. 41571436), the National Natural Science Foundation of China under Grant 91438203, the Hubei Province Science and Technology Support Program, China (Project No. 2015BAA027), the Jiangsu Province Science and Technology Support Program, China (Project No. BE2014866), and the South Wisdom Valley Innovative Research Team Program.
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Li, K., Yao, J., Li, L., Liu, Y. (2017). 3D Line Segment Reconstruction in Structured Scenes via Coplanar Line Segment Clustering. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10117. Springer, Cham. https://doi.org/10.1007/978-3-319-54427-4_4
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