Abstract
Advanced driver assistance using cameras is a first important step towards autonomous driving tasks. However, the computational power in automobiles is highly limited and hardware platforms with enormous processing resources such as GPUs are not available in serial production vehicles. In our paper we address the need for a highly efficient fusion method that is well suited for standard CPUs.
We assume that a number of pairwise disparity maps are available, which we project to a reference view pair and fuse them efficiently to improve the accuracy of the reference disparity map. We estimate a probability density function of disparities in the reference image using projection uncertainties. In the end the most probable disparity map is selected from the probability distribution.
We carried out extensive quantitative evaluations on challenging stereo data sets and real world images. These results clearly show that our method is able to recover very accurate disparity maps in real-time.
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References
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. In: ICCV, pp. 377–384 (1999)
Collins, R.T.: A space-sweep approach to true multi-image matching. In: CVPR, p. 358 (1996)
Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient belief propagation for early vision. IJCV 70(1), 41–54 (2006)
Gargallo, P., Sturm, P.: Bayesian 3D modeling from images using multiple depth maps. In: CVPR, pp. 885–891 (2005)
Hirschmüller, H.: Accurate and efficient stereo processing by semi-global matching and mutual information. In: CVPR, pp. 807–814 (2005)
Hirschmüller, H., Innocent, P.R., Garibaldi, J.: Real-time correlation-based stereo vision with reduced border errors. IJCV 47(1-3), 229–246 (2002)
Hirschmuüller, H.: Stereo vision in structured environments by consistent semi-global matching. In: CVPR, pp. 2386–2393 (2006)
Hosni, A., Bleyer, M., Gelautz, M., Rhemann, C.: Local stereo matching using geodesic support weights. In: ICIP (2009)
Koch, R., Pollefeys, M., Van Gool, L.: Multi Viewpoint Stereo from Uncalibrated Video Sequences. In: Burkhardt, H.-J., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1406, pp. 55–71. Springer, Heidelberg (1998)
Kolmogorov, V., Zabih, R.: Multi-camera Scene Reconstruction via Graph Cuts. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part III. LNCS, vol. 2352, pp. 82–96. Springer, Heidelberg (2002)
Merrell, P., Akbarzadeh, A., Wang, L., Frahm, J.M., Yang, R., Nistér, D.: Real-time visibility-based fusion of depth maps. In: ICCV, pp. 1–8 (2007)
Okutomi, M., Kanade, T.: A multiple-baseline stereo. PAMI 15(1), 353–363 (1993)
Sato, T., Kanbara, M., Yokoya, N., Takemura, H.: Dense 3-D reconstruction of an outdoor scene by hundreds-baseline stereo using a hand-held video camera. IJCV 47, 119–129 (2002)
Scharstein, D., Szeliski, R., Zabih, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV 47, 7–42 (2002)
Seitz, S.M., Curless, B., Diebel, J., Scharstein, D., Szeliski, R.: A comparison and evaluation of multi-view stereo reconstruction algorithms. In: CVPR (2006)
Szeliski, R.: A multi-view approach to motion and stereo. In: CVPR, p. 1157 (1999)
Unger, C., Benhimane, S., Wahl, E., Navab, N.: Efficient disparity computation without maximum disparity for real-time stereo vision. In: BMVC (2009)
Zach, C.: Fast and high quality fusion of depth maps. In: 3DPVT (2008)
Zhang, G., Jia, J., Wong, T.T., Bao, H.: Consistent depth maps recovery from a video sequence. PAMI 31(6), 974–988 (2009)
Zitnick, L.C., Kang, S.B., Uyttendaele, M., Winder, S., Szeliski, R.: High-quality video view interpolation using a layered representation. In: SIGGRAPH (2004)
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Unger, C., Wahl, E., Sturm, P., Ilic, S. (2012). Stereo Fusion from Multiple Viewpoints. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_47
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DOI: https://doi.org/10.1007/978-3-642-32717-9_47
Publisher Name: Springer, Berlin, Heidelberg
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