Abstract
This work combines two active areas of research in computer vision: unsupervised object extraction from a single image, and depth estimation from a stereo image pair. A recent, successful trend in unsupervised object extraction is to exploit so-called “3D scene-consistency”, that is enforcing that objects obey underlying physical constraints of the 3D scene, such as occupancy of 3D space and gravity of objects. Our main contribution is to introduce the concept of 3D scene-consistency into stereo matching. We show that this concept is beneficial for both tasks, object extraction and depth estimation. In particular, we demonstrate that our approach is able to create a large set of 3D scene-consistent object proposals, by varying e.g. the prior on the number of objects. After automatically ranking the proposals we show experimentally that our results are considerably closer to ground truth than state-of-the-art techniques which either use stereo or monocular images. We envision that our method will build the front-end of a future object recognition system for stereo images.
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Bleyer, M., Rother, C., Kohli, P., Scharstein, D., Sinha, S.: Object stereo - joint stereo matching and object segmentation. In: CVPR 2011 (2011)
Izadi, S., Agarwal, A., Criminisi, A., Winn, J., Blake, A., Fitzgibbon, A.: C-slate: Exploring rem. collaboration on horiz. multi-touch surfaces. In: Tabletop (2007)
Ladicky, L., Sturgess, P., Russell, C., Sengupta, S., Bastanlar, Y., Clocksin, W., Torr, P.: Joint optimisation for object class segmentation and dense stereo reconstruction. In: BMVC (2010)
Price, B., Cohen, S.: Stereocut: Consistent interactive object selection in stereo image pairs. In: ICCV (2011)
Björkman, M., Kragic, D.: Active 3d scene segmentation and detection of unknown objects. In: Conference on Robotics and Automation (2010)
Björkman, M., Kragic, D.: Active 3d segmentation through fixation of previously unseen objects. In: BMVC (2010)
Gupta, A., Efros, A., Hebert, M.: Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 482–496. Springer, Heidelberg (2010)
Ion, A., Carreira, J., Sminchisescu, C.: Image segmentation by discounted cumulative ranking on maximal cliques. In: ICCV (2011)
Hoiem, D., Efros, A., Hebert, M.: Putting objects in perspective. In: IJCV (2008)
Carreira, J., Sminchisescu, C.: Constrained parametric min-cuts for automatic object segmentation. In: PAMI (2012)
Endres, I., Hoiem, D.: Category Independent Object Proposals. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part V. LNCS, vol. 6315, pp. 575–588. Springer, Heidelberg (2010)
Carreira, J., Li, F., Sminchisescu, C.: Object recognition by sequential figure-ground ranking. IJCV (2012)
Bleyer, M., Rhemann, C., Rother, C.: Patchmatch stereo - stereo matching with slanted support windows. In: BMVC (2011)
Yoon, K., Kweon, I.: Locally adaptive support-weight approach for visual correspondence search. In: CVPR (2005)
Rhemann, C., Hosni, A., Bleyer, M., Rother, C., Gelautz, M.: Fast cost-volume filtering for visual correspondence and beyond. In: CVPR (2011)
Delong, A., Osokin, A., Isack, H., Boykov, Y.: Fast approximate energy minimization with label costs. In: CVPR (2010)
Christoudias, C., Georgescu, B., Meer, P.: Synergism in low-level vision. In: ICPR, vol. 4, pp. 150–155 (2002)
Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: From contours to regions: An empirical evaluation. In: CVPR (2009)
Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV 47, 7–42 (2002)
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Bleyer, M., Rhemann, C., Rother, C. (2012). Extracting 3D Scene-Consistent Object Proposals and Depth from Stereo Images. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds) Computer Vision – ECCV 2012. ECCV 2012. Lecture Notes in Computer Science, vol 7576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33715-4_34
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DOI: https://doi.org/10.1007/978-3-642-33715-4_34
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