Aisbett, J. 1989.Optical-flow with an intensity-weighted smoothing. IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society Press,11(5):512-522.
Anandan, P. 1989.A computational framework and an algorithm for the measurement of visual motion. International Journal of Computer Vision,2:283-310.
Axelsson, O. and Barker, V.A. 2001.Finite element solution of boundary value problems: Theory and computation. SIAM Classics in Applied Mathematics, 35.
Barron, J.L., Fleet, D.J., and Beauchemin, S.S. 1994.Performance of optical flowtechniques. International Journal of Computer Vision,12(l):43-77.
Bartolini, F. and Piva, A. 1997.Enhancement of the Horn and Schunck optic flow algorithm by means of median filters. In IEEE Proceedings Thirteenth International Conference on Digital Signal Processing (DSP 1997) IEEE Computer Society Press, 1,2:503-506.
Battiti, R., Amaldi, E., and Koch, C. 1991.Computing optical flow across multiple scales: An adaptive coarse-to-fine strategy. International Journal of Computer Vision,6(2):133-145.
Beauchemin, S.S. and Barron, J.L. 1995.The computation of optical flow. ACM Computing Surveys, 27(3):433-467
Benayoun, S. and Ayache, N. 1998.Dense non-rigid motion estimation in sequences of medical images using differential constraints. International Journal of Computer Vision,26(1):25-40.
Bergen, J.R., Burt, P.J., Hingorani, R., and Peleg, S. 1990.Computing two motions from three frames. In Proceedings of the Third International Conference on Computer Vision (ICCV 1990)Osaka, Japan, 27-32.
Black, M.J. and Anandan, P. 1996.The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields. Computer Vision and Image Understanding,63(1):75-104.
Celasun, I., Tekalp, A.M., Gokcetekin, M.H., and Harmanci, D.M. 2001.2-D mesh-based video object segmentation and tracking with occlusion resolution. Signal Processing: Image Communication,16:949-962.
Choi, J.G. and Kim, S.D. 1996.Multi-stage segmentation of optical flow field. Signal In Processing,54:109-118.
Cohen, I. and Herlin, I. 1999.Non uniform multiresolution method for optical flow and phase portrait models: Environmental applications. International Journal of Computer Vision,33(l):1-22
Condell, J.V., Scotney, B.W., and Morrow, P.J. 2001a. Estimation of motion through inverse finite element methods with triangular meshes. In Proceedings of the Ninth International Conference on Computer Analysis of Images and Patterns (CAIP 2001),Warsaw, Poland, Lecture Notes on Computer Science, vol. 2124, pp. 333-340.
Condell, J.V., Scotney, B.W., and Morrow, P.J. 2001b. Motion estimation through inverse finite element methods based on triangular meshes: Towards automatic region detection. In Proceedings of the Irish Machine Vision and Image Processing Conference (IMVIP 2001)Maynooth, Ireland, pp. 53-60.
Devlaminck, V. 1995.Finite element method for non-rigid motion estimation. In Proceedings of the SPIE International Society of Optical Engineering,2588:312-319.
Enkelmann, W. 1988.Investigations of multigrid algorithms for the estimation of optical flow fields in image sequences. Computer Vision, Graphics and Image Processing,43(2):150-177.
Fennema, C.L. and Thompson, W.B. 1979.Velocity determination in scenes containing several moving objects. Computer Graphics and Image Processing,9(4):301-315.
Fleet, D.J. and Jepson, A.D. 1989.Computation of normal velocity from local phase information. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (GVPR 1989), San Diego, California, USA, pp. 379-386.
Garcia, M.A., Vintimilla, B.X., and Sappa, A.D. 1999.Approximation of intensity images with adaptive triangular meshes: Towards a processable compressed representation. In Proceedings of the Third Irish Machine Vision and Image Processing Conference (IMVIP 1999), Dublin, Ireland, pp. 241-249.
Giachetti, A. and Torre, V. 1996.Refinement of optical flow estimation and detection of motion edges. In Proceedings of the Fourth European Conference on Computer Vision (ECCV 1996), Cambridge, UK, pp. 151-160.
Goh, W.B. and Martin, G.R. 1994.Model-based multiresolution motion estimation in noisy images. CVGIP Image Understanding,59(3):307-319.
Graham, J.V., Scotney, B.W., and Morrow, P.J. 2000a. Inverse finite element formulations for the computation of optical flow. In Proceedings of the Fourth Irish Machine Vision and Image Processing Conference (IMVIP 2000)Belfast, Northern Ireland, pp. 59-66.
Graham, J.V., Scotney, B.W., and Morrow, P.J. 2000b. Evaluation of inverse finite element techniques for gradient based motion estimation. In Proceedings of the Third IMA Conference on Imaging and Digital Image Processing, Leicester, UK.
Hata, N., Nabavi, A. Warfield, S., Wells, W., Kikinis, R., and Jolesz, F.A. 1999.A volumetric optical flow method for measurement of brain deformation from intraoperative magnetic resonance images. In Second International Conference on Medical Image Computing and Computer-Assisted Intervention, (MICCAI 1999), Cambridge, UK, Lecture Notes in Computer Science, vol. 1679, pp. 928-933.
Heeger, D.J. 1987.Model for the extraction of image flow. Journal of the Optical Society of America A-Optics Image Science and Vision,4(8):1455-1471.
Horn, B.K.P, and Schunck, B.G. Determining optical flow. Artificial Intelligence,17:185-203.
Hwang, S.H. and Lee, S.U. 1993.A hierarchical optical flow estimation algorithm based on the interlevel motion smoothness constraint. Pattern Recognition,26(6):939-952.
Illgner, K. and Müller, F. 1997.Image segmentation using motion estimation. Time-Varying Image Processing and Moving Object Recognition,4:238-243.
Kirchner, H. and Niemann, H. 1992.Finite element method for determination of optical flow. Pattern Recognition Letters,13:131-141.
Lucas, B. and Kanade, T. 1981.An iterative image registration technique with an application to stereo vision. In Proceedings of the Seventh International Joint Conference on Artificial Intelligence (IJCAI 1981),Vancouver, British Columbia, Canada, pp. 674-679.
Memin, E. and Perez, P. 1998.A multigrid approach for hierarchical motion estimation. In Sixth International Conference on Computer Vision (ICCV1998), Bombay, India, pp. 933-938.
Moulin, P., Krishnamurthy, R., and Woods, J.W. 1997.Multiscale modeling and estimation of motion fields for video coding. In IEEE Transactions on Image Processing,6(12):1606-1620.
Moulin, P. and Loui, A. 1993.Application of a multiresolution optical-flow-based method for motion estimation to video coding. In Proceedings of the 1993 IEEE International Symposium on Circuits and Systems,1:1-4.
Nagel, H.H. 1983.Displacement vectors derived from second order intensity variations in image sequences. Computer Vision, Graphics and Image Processing,21(1):85-117.
Odobez, J.M. and Bouthemy, P. 1994.Robust multiresolution estima-tion of parametric motion models in complex image sequences. In Proceedings of the Seventh European Conference on Signal Processing, (EUSIPCO 1994), Edinburgh, Scotland, pp. 411-415.
Ong, E.P. and Spann, M. 1999.Robust optical flow computation based on least-median-of-squares regression. International Journal of Computer Vision,31(1):51-82.
Schnörr, C. 1991.Determining optical flow for irregular domains by minimizing quadratic functionals of a certain class. International Journal of Computer Vision,6(1):25-38.
Scotney, B.W. 1991.Construction and analysis of petrov-galerkin approximations for convection-dominated flows. In Proceedings Thirteenth World Congress on Computation and Applied Mathematics, Dublin, IMACS, R.Vichnevetsky and J.J.H. Miller, (Eds.), pp. 505-507.
Szeliski, R. and Shum, H.Y. 1996.Motion estimation with quadtree splines. IEEE Transactions on Pattern Analysis and Machine In-telligence,18(12):1199-1210.
Terzopoulos, D. 1986.Image analysis using multigrid relaxation methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(2):129-139.
Wang, Y. and Lee, O. 1996.Use of two-dimensional deformable mesh structures for video coding, Part I-The synthesis problem: Mesh-based function approximation and mapping. IEEE Transactions on Circuits and Systems for Video Technology.6(6):636-646.
Weber, J. and Malik, J. 1995.Robust computation of optical flow in a multiscale differential framework. International Journal of Computer Vision,14(1):67-81.
Weickert, J. and Schnörr, C. 2001.A theoretical framework for convex regularizers in pde-based computation of image motion. International Journal of Computer Vision, 45(3):245-264.
Wu, S.F and Kittler, J. 1993.A gradient-based method for general motion estimation and segmentation. Journal of Visual Communication and Image Representation,4(1):25-38.
Xie, K., Eycken, L.V., and Oosterlinck, A. 1996.Hierarchical motion estimation with smoothness constraint and postprocessing. Optical Engineering,35(1):145-155.
Yaacobson, F.S. and Givoli, D. 1998.An adaptive finite element procedure for the image segmentation problem. Communications of Numerical Methods in Engineering,14:621-632.
Yang, Y., Wernick, M.N., and Brankov, J.G. 2001.A fast algorithm for accurate content-adaptive mesh generation. IEEE International Conference on Image Processing (ICIP 2001), Thessaloniki, Greece, pp. 868-871.