Direct Recovery of Motion and Shape in the General Case by Fixation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Estimation of Motion Vector Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion compensated film restoration
Machine Vision and Applications
Image Registration under Varying Illumination: Hyper-Demons Algorithm
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
A General PDE-Framework for Registration of Contrast Enhanced Images
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Human action detection via boosted local motion histograms
Machine Vision and Applications
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Improved reconstruction of deforming surfaces by cancelling ambient occlusion
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
A Gauss-Newton approach to joint image registration and intensity correction
Computer Methods and Programs in Biomedicine
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Optical flow is the apparent (or perceived) motion of image brightness patterns arising from relative motion of objects and observer. Estimation of the optical flow requires the application of two kinds of constraint: the flow field {\it smoothness constraint} and the {\it brightness constancy constraint}. The brightness constancy constraint permits one to match image brightness values across images, but is very restrictive. We propose replacing this constraint with a more general constraint, which permits a linear transformation between image brightness values. The transformation parameters are allowed to vary smoothly so that inexact matching is allowed. We describe the implementation on a highly parallel computer and present sample results.