Computing Optical Flow via Variational Techniques

Defined as the apparent motion in a sequence of images, the optical flow is very important in the computer vision community where its accurate estimation is necessary for many applications. It is o...

[1]  C. Vogel,et al.  Analysis of bounded variation penalty methods for ill-posed problems , 1994 .

[2]  J J Koenderink,et al.  Affine structure from motion. , 1991, Journal of the Optical Society of America. A, Optics and image science.

[3]  Hans-Hellmut Nagel,et al.  Optical Flow Estimation: Advances and Comparisons , 1994, ECCV.

[4]  Hans-Hellmut Nagel,et al.  Direct Estimation of Optical Flow and of Its Derivatives , 1992 .

[5]  Patrick Pérez,et al.  A multigrid approach for hierarchical motion estimation , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[6]  G. Aubert,et al.  A mathematical study of the relaxed optical flow problem in the space BV (&Ω) , 1999 .

[7]  Richard P. Wildes,et al.  Physically based fluid flow recovery from image sequences , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  E. Giusti Minimal surfaces and functions of bounded variation , 1977 .

[9]  Michael J. Black Robust incremental optical flow , 1992 .

[10]  Richard P. Wildes,et al.  Physically Based Uid Ow Recovery from Image Sequences , 2008 .

[11]  G. D. Maso,et al.  An Introduction to-convergence , 1993 .

[12]  R. Deriche,et al.  Les EDP en traitement des images et vision par ordinateur , 1995 .

[13]  Paolo Nesi,et al.  Variational approach to optical flow estimation managing discontinuities , 1993, Image Vis. Comput..

[14]  L. Evans Measure theory and fine properties of functions , 1992 .

[15]  Michel Barlaud,et al.  Deterministic edge-preserving regularization in computed imaging , 1997, IEEE Trans. Image Process..

[16]  Pierre Charbonnier,et al.  Reconstruction d''image: R'egularization avec prise en compte des discontinuit'es , 1994 .

[17]  Frédéric Guichard,et al.  Accurate estimation of discontinuous optical flow by minimizing divergence related functionals , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[18]  Shahriar Negahdaripour,et al.  A generalized brightness change model for computing optical flow , 1993, 1993 (4th) International Conference on Computer Vision.

[19]  A. Verri,et al.  Differential techniques for optical flow , 1990 .

[20]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[21]  W. Ziemer Weakly differentiable functions , 1989 .

[22]  H. Brezis Opérateurs maximaux monotones et semi-groupes de contractions dans les espaces de Hilbert , 1973 .

[23]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[24]  Marco Mattavelli,et al.  Motion estimation relaxing the constancy brightness constraint , 1994, Proceedings of 1st International Conference on Image Processing.

[25]  Rachid Deriche,et al.  Nonlinear operators in image restoration , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[26]  Massimo Tistarelli,et al.  Computation of coherent optical flow by using multiple constraints , 1995, Proceedings of IEEE International Conference on Computer Vision.

[27]  P. Pérez,et al.  Dense Estimation and Object-Oriented Segmentation of the Optical Flow with Robust Techniques , 1996 .

[28]  N. Meyers An $L^p$-estimate for the gradient of solutions of second order elliptic divergence equations , 1963 .

[29]  Patrick Pérez,et al.  Dense estimation and object-based segmentation of the optical flow with robust techniques , 1998, IEEE Trans. Image Process..

[30]  Hans-Hellmut Nagel,et al.  On the Estimation of Optical Flow: Relations between Different Approaches and Some New Results , 1987, Artif. Intell..

[31]  Gary J. Balas,et al.  Optical flow: a curve evolution approach , 1996, IEEE Trans. Image Process..

[32]  Andrea J. van Doorn,et al.  Invariant Properties of the Motion Parallax Field due to the Movement of Rigid Bodies Relative to an Observer , 1975 .

[33]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[34]  Vincent Devlaminck,et al.  Estimation of compressible or incompressible deformable motions for density images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[35]  J. L. Webb OPERATEURS MAXIMAUX MONOTONES ET SEMI‐GROUPES DE CONTRACTIONS DANS LES ESPACES DE HILBERT , 1974 .

[36]  Yee-Hong Yang,et al.  Experimental evaluation of motion constraint equations , 1991, CVGIP Image Underst..

[37]  H. Fédérer Geometric Measure Theory , 1969 .

[38]  Jerry L. Prince,et al.  On div-curl regularization for motion estimation in 3-D volumetric imaging , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[39]  Sugata Ghosal,et al.  A Fast Scalable Algorithm for Discontinuous Optical Flow Estimation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[40]  Rachid Deriche,et al.  Optical-Flow Estimation while Preserving Its Discontinuities: A Variational Approach , 1995, ACCV.

[41]  P. Lions,et al.  Image recovery via total variation minimization and related problems , 1997 .

[42]  N. Meyers,et al.  Some results on regularity for solutions of non-linear elliptic systems and quasi-regular functions , 1975 .

[43]  A. N. Tikhonov,et al.  Solutions of ill-posed problems , 1977 .

[44]  Giuseppe Buttazzo,et al.  Semicontinuity, Relaxation and Integral Representation in the Calculus of Variations , 1989 .

[45]  Levent Onural,et al.  Gibbs random field model based 3-D motion estimation by weakened rigidity , 1994, Proceedings of 1st International Conference on Image Processing.

[46]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[47]  L. Vese,et al.  A Variational Method in Image Recovery , 1997 .

[48]  L. Ambrosio,et al.  Approximation of functional depending on jumps by elliptic functional via t-convergence , 1990 .

[49]  Patrick Bouthemy,et al.  Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[50]  Tomaso A. Poggio,et al.  Motion Field and Optical Flow: Qualitative Properties , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[51]  Luc Van Gool,et al.  Determination of Optical Flow and its Discontinuities using Non-Linear Diffusion , 1994, ECCV.

[52]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[53]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[54]  P. Clarysse,et al.  Estimation du flot optique en présence de discontinuités : une revue , 1996 .

[55]  J. Serrin,et al.  Sublinear functions of measures and variational integrals , 1964 .

[56]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.