Computation of component image velocity from local phase information
International Journal of Computer Vision
Distributed representation and analysis of visual motion
Distributed representation and analysis of visual motion
Performance of optical flow techniques
International Journal of Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Spatial and Fourier Error Minimization for Motion Estimation and Segmentation
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Two Applications of Graph-Cuts to Image Processing
DICTA '08 Proceedings of the 2008 Digital Image Computing: Techniques and Applications
On the optimality of solutions of the max-product belief-propagation algorithm in arbitrary graphs
IEEE Transactions on Information Theory
Analysis of Superimposed Oriented Patterns
IEEE Transactions on Image Processing
A phase-based approach to the estimation of the optical flow field using spatial filtering
IEEE Transactions on Neural Networks
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A novel Fourier-based technique for local motion detection from image sequences is proposed. In this method, the instantaneous velocities of local image points are inferred directly from the global 3D Fourier components of the image sequence. This is done by selecting those velocities for which the superposition of the corresponding Fourier gratings leads to constructive interference at the image point. Hence, image velocities can be assigned locally even though position is computed from the phases and amplitudes of global Fourier components (spanning the whole image sequence) that have been filtered based on the motion-constraint equation, reducing certain aperture effects typically arising from windowing in other methods. Regularization is introduced for sequences having smooth flow fields. Aperture effects and their effect on optic-flow regularization are investigated in this context. The algorithm is tested on both synthetic and real image sequences and the results are compared to those of other local methods. Finally, we show that other motion features, i.e. motion direction, can be computed using the same algorithmic framework without requiring an intermediate representation of local velocity, which is an important characteristic of the proposed method.