Abstract
We introduce a novel image defencing method suitable for consumer photography, where plausible results must be achieved under common camera settings. First, detection of lattices with see-through texels is performed in an iterative process using online learning and classification from intermediate results to aid subsequent detection. Then, segmentation of the foreground is performed using accumulated statistics from all lattice points. Next, multi-view inpainting is performed to fill in occluded areas with information from shifted views where parts of the occluded regions may be visible. For regions occluded in all views, we use novel symmetry-augmented inpainting, which combines traditional texture synthesis with an increased pool of candidate patches found by simulating bilateral symmetry patterns from the source image. The results show the effectiveness of our proposed method.
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References
Liu, Y., Belkina, T., Hays, J., Lublinerman, R.: Image de-fencing. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, Anchorage, Alaska, pp. 1–8 (2008)
Hays, J., Leordeanu, M., Efros, A.A., Liu, Y.: Discovering texture regularity as a higher-order correspondence problem. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 522–535. Springer, Heidelberg (2006)
Criminisi, A., Perez, P., Toyama, K.: Object removal by exemplar-based inpainting. In: CVPR, pp. 721–728 (2003)
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)
Park, M., Collins, R.T., Liu, Y.: Deformed Lattice Discovery via Efficient Mean-Shift Belief Propagation. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 474–485. Springer, Heidelberg (2008)
Liu, Y., Collins, R.T., Tsin, Y.: A computational model for periodic pattern perception based on frieze and wallpaper groups. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 354–371 (2004)
Leung, T., Malik, J.: Detecting, localizing and grouping repeated scene elements from an image. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1065, pp. 546–555. Springer, Heidelberg (1996)
Schaffalitzky, F., Zisserman, A.: Geometric grouping of repeated elements within images. In: Shape, Contour and Grouping in Computer Vision, pp. 165–181 (1999)
Han, J., McKenna, S., Wang, R.: Regular texture analysis as statistical model selection. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 242–255. Springer, Heidelberg (2008)
Lin, H.C., Wang, L.L., Yang, S.N.: Extracting periodicity of a regular texture based on autocorrelation functions. Pattern Recognition Letters, 433–443 (1997)
Leonard, G.O.H., Takeo, K.: Computer analysis of regular repetitive textures. In: Proceedings of a Workshop on Image Understanding Workshop. Morgan Kaufmann Publishers Inc., San Francisco (1989)
Favaro, P., Grisan, E.: Defocus inpainting. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 349–359. Springer, Heidelberg (2006)
Wexler, Y., Shechtman, E., Irani, M.: Space-time completion of video. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 463–476 (2007)
Patwardhan, K.A., Sapiro, G., Bertalmio, M.: Video inpainting of occluding and occluded objects. In: IEEE International Conference on Image Processing, ICIP 2005, vol. 2, pp. 69–II–72 (2005)
James, H., Alexei, A.E.: Scene completion using millions of photographs, 1276382 4 (2007)
Vaish, V., Levoy, M., Szeliski, R., Zitnick, C.L., Sing Bing, K.: Reconstructing occluded surfaces using synthetic apertures: Stereo, focus and robust measures. In: Computer Vision and Pattern Recognition, vol. 2, pp. 2331–2338 (2006)
Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proc. of 7th International Joint Conference on Artificial Intelligence (IJCAI), pp. 674–679 (1981)
Park, M., Lee, S., Chen, P.C., Kashyap, S., Butt, A.A., Liu, Y.: Performance evaluation of state-of-the-art discrete symmetry detection algorithms. In: Proceedings of CVPR 2008 (2008)
Chen, P.C., Hays, J.H., Lee, S., Park, M., Liu, Y.: A quantitative evaluation of symmetry detection algorithms. Technical Report CMU-RI-TR-07-36, Robotics Institute, Pittsburgh, PA (2007)
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Park, M., Brocklehurst, K., Collins, R.T., Liu, Y. (2011). Image De-fencing Revisited. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19282-1_34
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DOI: https://doi.org/10.1007/978-3-642-19282-1_34
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