Accessibility navigation


Motion estimation through approximated densities

Ruiz, V. F. and Skodras, A. (1997) Motion estimation through approximated densities. In: Proceedings of 13th International Conference on Digital Signal Processing. IEEE, pp. 805-808. ISBN 0780341376

Full text not archived in this repository.

To link to this article DOI: 10.1109/ICDSP.1997.628475

Abstract/Summary

Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block-matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. The Kalman filtering technique applicability for block-based motion estimation is rather limited due to discontinuities in the dynamic behaviour of the motion vectors. Therefore, we propose an application of the concept of the filtering by approximated densities (FAD). The FAD, originally introduced to alleviate limitations due to conventional Kalman modelling, is applied to interframe block-motion estimation. This application uses a simple form of FAD involving statistical characteristics of multi-modal distributions up to second order.

Item Type:Book or Report Section
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:19015
Uncontrolled Keywords:Kalman filtering, Kalman modelling, algorithms, approximated densities, block-based motion estimation, block-matching, coarse search algorithm, filtering by approximated densities, interframe block-motion estimation, motion vectors, multi-modal distributions, nonlinear adaptive filtering, second order distributions, statistical characteristics, video compression, video sequences
Publisher:IEEE

Centaur Editors: Update this record

Page navigation