Abstract
Object removal and inpainting approaches typically require a user to manually create a mask around occluding objects. While creating masks for a small number of images is possible, it rapidly becomes untenable for longer image sequences. Instead, we accomplish this step automatically using an object detection framework to explicitly recognize and remove several classes of occlusions. We propose using this technique to improve 3D urban reconstruction from street level imagery, in which building facades are frequently occluded by vegetation or vehicles. By assuming facades in the background are planar, 3D scene estimation provides important context to the inpainting process by restricting input sample patches to regions that are coplanar to the occlusion, leading to more realistic final textures. Moreover, because non-static and reflective occlusion classes tend to be difficult to reconstruct, explicitly recognizing and removing them improves the resulting 3D scene.
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References
Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.B.: PatchMatch: A randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics (Proc. SIGGRAPH) 28(3) (August 2009)
Benitez, S., Denis, E., Baillard, C.: Automatic production of occlusion-free rectified facade textures using vehicle-based imagery. In: Photogrammetric Computer Vision and Image Analysis, p. A:275 (2010)
Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(9), 1124–1137 (2004)
Criminisi, A., Perez, P., Toyama, K.: Region filling and object removal by exemplar-based image inpainting. IEEE Transactions on Image Processing 13, 1200–1212 (2004)
Dick, A.R., Torr, P.H.S., Cipolla, R.: Modelling and interpretation of architecture from several images. Int. J. Comput. Vision 60, 111–134 (2004)
Felzenszwalb, P., Girshick, R., McAllester, D.: Cascade object detection with deformable part models. In: Computer Vision and Pattern Recognition (2010)
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004) ISBN: 0521540518
Hedau, V., Hoiem, D., Forsyth, D.: Recovering the spatial layout of cluttered rooms. In: International Conference on Computer Vision (2009)
Hoiem, D., Efros, A.A., Hebert, M.: Putting objects in perspective. International Journal of Computer Vision 80(1), 3–15 (2008)
Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, SGP 2006, pp. 61–70. Eurographics Association, Aire-la-Ville (2006)
Konushin, V., Vezhnevets, V.: Abstract automatic building texture completion. Graphicon (2007)
Leibe, B., Leonardis, A., Schiele, B.: Robust object detection with interleaved categorization and segmentation. International Journal of Computer Vision 77(1-3), 259–289 (2008)
Rasmussen, C., Korah, T., Ulrich, W.: Randomized view planning and occlusion removal for mosaicing building facades. In: IEEE International Conference on Intelligent Robots and Systems (2005), http://nameless.cis.udel.edu/pubs/2005/RKU05
Rother, C., Kolmogorov, V., Blake, A.: ”grabcut”: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23, 309–314 (2004)
Saxena, A., Chung, S.H., Ng, A.Y.: 3-d depth reconstruction from a single still image. International Journal of Computer Vision, IJCV 76 (2007)
Thomas, A., Ferrari, V., Leibe, B., Tuytelaars, T., Van Gool, L.: Shape-from-recognition: Recognition enables meta-data transfer. Computer Vision and Image Understanding 113(12), 1222–1234 (2009)
Thomas, A., Ferrari, V., Leibe, B., Tuytelaars, T., Schiele, B., Van Gool, L.: Towards multi-view object class detection. In: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006, vol. 2, pp. 1589–1596. IEEE Computer Society, Washington, DC, USA (2006)
Vergauwen, M., Van Gool, L.: Web-based 3d reconstruction service. Mach. Vision Appl. 17(6), 411–426 (2006)
Wang, L., Jin, H., Yang, R., Gong, M.: Stereoscopic inpainting: Joint color and depth completion from stereo images. In: Conference on Computer Vision and Pattern Recognition (2008)
Werner, T., Zisserman, A.: Model selection for automated reconstruction from multiple views. In: British Machine Vision Conference, pp. 53–62 (2002)
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)
Xiao, J., Fang, T., Zhao, P., Lhuillier, M., Quan, L.: Image-based street-side city modeling. ACM Trans. Graph. 28, 114:1–114:12 (2009)
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Engels, C., Tingdahl, D., Vercruysse, M., Tuytelaars, T., Sahli, H., Van Gool, L. (2011). Automatic Occlusion Removal from Facades for 3D Urban Reconstruction. In: Blanc-Talon, J., Kleihorst, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2011. Lecture Notes in Computer Science, vol 6915. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23687-7_61
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DOI: https://doi.org/10.1007/978-3-642-23687-7_61
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