IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Reliable and Efficient Computation of Optical Flow
International Journal of Computer Vision
International Journal of Computer Vision
Reliable Estimation of Dense Optical Flow Fields with Large Displacements
International Journal of Computer Vision
Hierarchical Estimation and Segmentation of Dense Motion Fields
International Journal of Computer Vision
Skin and Bones: Multi-layer, Locally Affine, Optical Flow and Regularization with Transparency
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
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
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
High accuracy optical flow method based on a theory for warping: 3d extension
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
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We describe the implementation of a 2D optical flow algorithm published in the European Conference on Computer Vision (ECCV 2004) by Brox et al. [1] (best paper award) and a qualitative and quantitative evaluation of it for a number of synthetic and real image sequences. Their optical flow method combines three assumptions: a brightness constancy assumption, a gradient constancy assumption and a spatio-temporal smoothness constraint. A numerical scheme based on fixed point iterations is used. Their method uses a coarse-to-fine warping strategy to measure larger optical flow vectors. We have investigated the algorithm in detail and our evaluation of the method demonstrates that it produces very accurate optical flow fields from only 2 input images.