Optical Flow with an Intensity-Weighted Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation and analysis of image motion: a synopsis of current problems and methods
International Journal of Computer Vision
Global optimal image reconstruction from blurred noisy data by a Bayesian approach
Journal of Optimization Theory and Applications
Fast Local and Global Projection-Based Methods for Affine Motion Estimation
Journal of Mathematical Imaging and Vision
Motion estimation for region-based video coding
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
The Dense Estimation of Motion and Appearance in Layers
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 11 - Volume 11
Filtering image sequences from a moving object and the edge detection problem
Computers & Mathematics with Applications
Object-based estimation of dense motion fields
IEEE Transactions on Image Processing
3-D Kalman filter for image motion estimation
IEEE Transactions on Image Processing
Two-dimensional matched filtering for motion estimation
IEEE Transactions on Image Processing
Filtering requirements for gradient-based optical flow measurement
IEEE Transactions on Image Processing
Modeling for edge detection problems in blurred noisy images
IEEE Transactions on Image Processing
Nonuniform image motion estimation using Kalman filtering
IEEE Transactions on Image Processing
A fast rate-optimized motion estimation algorithm for low-bit-rate video coding
IEEE Transactions on Circuits and Systems for Video Technology
Quadtree-structured variable-size block-matching motion estimation with minimal error
IEEE Transactions on Circuits and Systems for Video Technology
Kalman filtering based rate-constrained motion estimation for very low bit rate video coding
IEEE Transactions on Circuits and Systems for Video Technology
Adaptive motion-compensated filtering of noisy image sequences
IEEE Transactions on Circuits and Systems for Video Technology
Motion identification from image sequences: Information theory and pixel selection
Computers & Mathematics with Applications
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In this paper the problem of online motion and deformation estimation from a sequence of degraded images is considered. More specifically we have considered the superposition of a rigid motion and an affine deformation, while the considered degradation consists in a blurring effect and an additive noise. The measurement equation is heavily nonlinear with respect to motion parameters. Therefore, in order to process the pixels of each frame of the sequence, a filtering procedure is proposed, which includes a linear approximation. The proposed procedure has been widely tested against simulated data and also with reference to an experiment with real data. The obtained results turn out to be quite satisfactory.