iccv iccv2013 iccv2013-397 iccv2013-397-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Tali Dekel_(Basha), Yael Moses, Shai Avidan
Abstract: Photo-sequencing is the problem of recovering the temporal order of a set of still images of a dynamic event, taken asynchronously by a set of uncalibrated cameras. Solving this problem is a first, crucial step for analyzing (or visualizing) the dynamic content of the scene captured by a large number of freely moving spectators. We propose a geometric based solution, followed by rank aggregation to . ac . i l avidan@ eng .t au . ac . i l the photo-sequencing problem. Our algorithm trades spatial certainty for temporal certainty. Whereas the previous solution proposed by [4] relies on two images taken from the same static camera to eliminate uncertainty in space, we drop the static-camera assumption and replace it with temporal information available from images taken from the same (moving) camera. Our method thus overcomes the limitation of the static-camera assumption, and scales much better with the duration of the event and the spread of cameras in space. We present successful results on challenging real data sets and large scale synthetic data (250 images).
[1] I. Akhter, Y. Sheikh, S. Khan, and T. Kanade. Trajectory space: A dual representation for nonrigid structure from motion. PAMI, 2011.
[2] S. Avidan and A. Shashua. Trajectory triangulation: 3d reconstruction of moving points from a monocular image sequence. PAMI, 2000.
[3] L. Ballan, G. Brostow, J. Puwein, and M. Pollefeys. Unstructured video-based rendering: Interactive exploration of casually captured videos. ACM (TOG), 2010.
[4] T. Basha, Y. Moses, and S. Avidan. Photo sequencing. ECCV, 2012.
[5] C. Bregler, A. Hertzmann, and H. Biermann. Recovering non-rigid 3d shape from image streams. In CVPR, 2000.
[6] C. Dwork, R. Kumar, M. Naor, and D. Sivakumar. Rank aggregation methods for the web. In IW3C2, 2001 .
[7] L. Goshen and I. Shimshoni. Balanced exploration and exploitation model search for efficient epipolar geometry estimation. In ECCV, 2006.
[8] Y. HaCohen, E. Shechtman, D. Goldman, and D. Lischinski. Non-rigid dense correspondence with applications for image enhancement. SIGGRAPH, 2011.
[9] R. Hartley and R. Vidal. Perspective nonrigid shape and motion recovery. In ECCV, pages 276–289, 2008.
[10] J.-Y. Kaminski and M. Teicher. A general framework for
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19] trajectory triangulation. JMIV, 2004. B. Meyer, T. Stich, M. Magnor, and M. Pollefeys. Subframe temporal alignment of non-stationary cameras. In BMVC, 2008. F. L. C. P ´adua, R. L. Carceroni, G. A. M. R. Santos, and K. N. Kutulakos. Linear sequence-to-sequence alignment. PAMI, 2010. H. Park, T. Shiratori, I. Matthews, and Y. Sheikh. 3d reconstruction of a moving point from a series of 2d projections. ECCV, 2010. D. Pundik and Y. Moses. Video synchronization using temporal signals from epipolar lines. In ECCV, 2010. G. Schindler and F. Dellaert. Probabilistic temporal inference on reconstructed 3d scenes. In CVPR, 2010. A. Shashua and L. Wolf. Homography tensors: On algebraic entities that represent three views of static or moving planar points. ECCV, 2000. N. Snavely, S. Seitz, and R. Szeliski. Photo tourism: exploring photo collections in 3d. In SIGGRAPH, 2006. C. Tomasi and T. Kanade. Shape and motion from image streams under orthography: a factorization method. IJCV, 1992. L. Wolf and A. Shashua. On projection matrices pk → p2, k=3,...,6 and their applications in computer vision. IJCV, 2002. 998844