Multiresolution elastic matching
Computer Vision, Graphics, and Image Processing
Performance of optical flow techniques
International Journal of Computer Vision
International Journal of Computer Vision
Diffeomorphisms Groups and Pattern Matching in Image Analysis
International Journal of Computer Vision
Computing optical flow via variational techniques
SIAM Journal on Applied Mathematics
Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Detecting and Tracking Multiple Moving Objects Using Temporal Integration
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Optical Flow Using Overlapped Basis Functions for Solving Global Motion Problems
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Discrete Wavelet Analysis: A New Framework for Fast Optic Flow Computation
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Fast Fluid Registration of Medical Images
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Dense estimation and object-based segmentation of the optical flow with robust techniques
IEEE Transactions on Image Processing
Optical Flow and Image Registration: A New Local Rigidity Approach for Global Minimization
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
A New Image Registration Technique with Free Boundary Constraints: Application to Mammography
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
A new image registration technique with free boundary constraints: application to mammography
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Medical Image Registration and Interpolation by Optical Flow with Maximal Rigidity
Journal of Mathematical Imaging and Vision
Image matching using alpha-entropy measures and entropic graphs
Signal Processing - Special section on content-based image and video retrieval
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
Algorithmic Differentiation: Application to Variational Problems in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beauty with variational methods: an optic flow approach to hairstyle simulation
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Translational photometric alignment of single-view image sequences
Computer Vision and Image Understanding
Local-global optical flow for image registration
iUBICOM'11 Proceedings of the 6th international conference on Ubiquitous and Collaborative Computing
Backtracking: Retrospective multi-target tracking
Computer Vision and Image Understanding
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We address the theoretical problems of optical flow estimation and image registration in a multi-scale framework in any dimension. Much work has been done based on the minimization of a distance between a first image and a second image after applying deformation or motion field. Usually no justification is given about convergence of the algorithm used. We start by showing, in the translation case, that convergence to the global minimum is made easier by applying a low pass filter to the images hence making the energy “convex enough”. In order to keep convergence to the global minimum in the general case, we introduce a local rigidity hypothesis on the unknown deformation. We then deduce a new natural motion constraint equation (MCE) at each scale using the Dirichlet low pass operator. This transforms the problem to solving the energy minimization in a finite dimensional subspace of approximation obtained through Fourier Decomposition. This allows us to derive sufficient conditions for convergence of a new multi-scale and iterative motion estimation/registration scheme towards a global minimum of the usual nonlinear energy instead of a local minimum as did all previous methods. Although some of the sufficient conditions cannot always be fulfilled because of the absence of the necessary a priori knowledge on the motion, we use an implicit approach. We illustrate our method by showing results on synthetic and real examples in dimension 1 (signal matching, Stereo) and 2 (Motion, Registration, Morphing), including large deformation experiments.