Subject: Computer Science - Computer Vision and Pattern Recognition
Current algorithmic approaches for piecewise affine motion estimation are based on alternating motion segmentation and estimation. We propose a new method to estimate piecewise affine motion fields directly without intermediate segmentation. To this end, we reformulate ... View more
 M. Bleyer, C. Rhemann, and M. Gelautz. Segmentation-based motion with occlusions using graph-cut optimization. In DAGM Symposium on Pattern Recognotion, pages 465-474, Berlin, Germany, September 2006.
 Patrick Bouthemy and Edouard François. Motion segmentation and qualitative dynamic scene analysis from an image sequence. Int. J. of Computer Vision, 10(2):157-182, 1993.
 Kristian Bredies, Karl Kunisch, and Thomas Pock. Total generalized variation. SIAM Journal on Imaging Sciences, 3(3):492-526, 2010.
 T. Brox, A. Bruhn, N. Papenberg, and J. Weickert. High accuracy optical flow estimation based on a theory for warping. In European Conference on Computer Vision (ECCV), pages 25-36, Prague, Czech Republic, 2004.
 T. Brox and J. Malik. Large displacement optical flow: descriptor matching in variational motion estimation. IEEE Trans. Pattern Analysis and Machine Intelligence, 33(3):500-513, 2011.
 D. Butler, J. Wul , G. Stanley, and M. Black. A naturalistic open source movie for optical flow evaluation. In European Conference on Computer Vision (ECCV), pages 611-625. Springer-Verlag, 2012.
 Xiaohao Cai, Jan Henrik Fitschen, Mila Nikolova, Gabriele Steidl, and Martin Storath. Disparity and optical flow partitioning using extended potts priors. Information and Inference, 4(1):43-62, 2015.
 A. Chambolle. Finite-di erences discretizations of the Mumford-Shah functional. ESAIM: Mathematical Modelling and Numerical Analysis, 33(02):261-288, 1999.
 A. Chambolle and T. Pock. A first-order primal-dual algorithm for convex problems with applications to imaging. Journal of Mathematical Imaging and Vision, 40(1):120-145, 2011.