[1] SUDIPTA N S, FRAHM J M, POLLEFEYS M, et al. Feature tracking and matching in video using programmable graphics hardware [J]. Machine Vision and Applications, 2011, 22(1): 207-217.
[2] HAYAKAWA H, SHIBATA T. Block-matching-based motion field generation utilizing directional edge displacement [J]. Computer and Electronic Engineering, 2010, 36(4): 617-625.
[3] SUNDARAM N, BROX T, KEUTZER K. Dense point trajectories by GPU-accelerated large displacement optical flow [J]. Lecture Notes in Computer Science, 2010, 6311: 438-451.
[4] BROX T, MALIK J. Large displacement optical flow: descriptor matching in variational motion estimation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2011, 33(3): 500-513.
[5] DUFAUX F, MOCCAGATTA I, MOSCHENI F, et al. Vector quantization-based motion field segmentation under the entropy criterion [J]. Journal of Vision Communication and Image Representation, 1994, 5(4): 356-369.
[6] PARAGIOS N, DERICHE R. Geodesic active regions and level set methods for motion estimation and tracking [J]. Computer Vision and Image Understanding, 2005, 97(3): 259-282.
[7] M'EMIN E, P'EREZ P. Hierarchical estimation and segmentation of dense motion fields [J]. International Journal of Computer Vision, 2002, 46(2): 129-155.
[8] FEGHALI R, MITICHE A. Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation [J]. IEEE Transactions on Image Processing, 2004, 13(11): 1473-1490.
[9] CASELLES V, KIMMELI R, SAPRIRO G. Geodesic active contours [J].International Journal of Computational Vision,1997,22(1): 61-79.
[10] CHAN T, VESE L. Active contours without edges [J].IEEE Transactions on Image Processing, 2001, 10(2): 266-277.
[11] BERTALMIO M, SAPIRO G, RANDALL G. Morphing active contour [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(7): 733-737.
[12] BESSON S J, BARLAUD M, AUBERT G. Detection and tracking of moving objects using a new level set based method [C]∥ Proceedings of International Conference on Pattern Recognition. Barcelona: [s.n.], 2000: 1100-1105.
[13] OSHER S, SETHIAN J. Fronts propagating with curvature dependent speed: algorithms based on the Hamilton-Jacobi formulation [J]. Journal of Computational Physics,1988,79(1): 1249.
[14] CHAN T F, ESEDO GLU S, NIKOLOVA M. Algorithms for finding global minimizers of image segmentation and denoising models [J]. SIAM Journal of Applied Mathematics, 2006, 66(5): 1632-1648.
[15] BRESSON X, ESEDOGLU S, VANDERGHEYNST P, et al. Fast global minimization of the active contour/snake models [J]. Journal of Mathematical Imaging and Vision, 2007, 28(2): 151-167.
[16] GOLDSTEIN T, BRESSON X, OSHER S. Geometric applications of the split Bregman method: segmentation and surface reconstruction \ [J\]. Journal of Scientific Computing, 2010,45: 272-293.
[17] BOYKOV Y, FUNKA-LEA G. Graph cuts and ecient N-D image segmentation [J]. International Journal of Computer Vision (IJCV), 2006, 70(2): 109-131.
[18] BOYKOV Y, KOLMOGOROV V. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(9): 1124-1137.
[19] RUDIN L I, OSHER S, FATEMI E. Nonlinear total variation based noise removal algorithms [J]. Physica D: Nonlinear Phenomena, 1992, 60(1/2/3/4): 259-268.
[20] CHAMBOLLE A. An algorithm for total variation minimization and applications [J]. Journal of Mathematical Imaging and Vision, 2004, 20(1/2): 89-97.
[21] TONY C, GOLUB G H, MULET P. A nonlinear primal-dual method for total variation-based image restoration [J]. SIAM Journal on Scientific Computing, 1999, 20: 1964-1977.
[22] WANG S Y, YU H M, ROLAND H. 3D Video based segentation and motion estimation with active surface evolution [J]. Journal of Signal Processing Systems, 2013, 71(1): 21-34.
[23] WANG S Y, YU H M. A variational approach for ego-motion estimation and segmentation based on 3D TOF camera [C]∥4th International Congress on Image and Signal Processing. Shanghai: IEEE, 2011: 1174-1178. |