Title: Motion estimation using the total variation-local-global optical flow and the structure-texture image decomposition

Authors: Insaf Bellamine; Hamid Tairi

Addresses: LIAN, Department of Computer Science, Sidi Mohamed Ben Abdellah University, BP 1796, Fez, Morocco ' LIAN, Department of Computer Science, Sidi Mohamed Ben Abdellah University, BP 1796, Fez, Morocco

Abstract: Motion estimation is currently approximated by the visual displacement field called optical flow. The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. Actually, several methods are used to estimate the optical flow, but a good compromise between computational cost and accuracy is hard to achieve. This work presents a combined local-global-total variation (CLG-TV) approach with structure-texture image decomposition. The combination is used to control the propagation phenomena and to gain robustness against illumination changes, influence of texture on the results and sensitivity to outliers. The resulting method is able to compute larger displacements in a reasonable time.

Keywords: motion estimation; structure-texture image decomposition; optical flow; local-global-total variation; image processing; propagation phenomena; illumination changes.

DOI: 10.1504/IJCAT.2016.073609

International Journal of Computer Applications in Technology, 2016 Vol.53 No.1, pp.41 - 50

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 13 Dec 2015 *

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