Motion estimation using the total variation-local-global optical flow and the structure-texture image decomposition Online publication date: Mon, 14-Dec-2015
by Insaf Bellamine; Hamid Tairi
International Journal of Computer Applications in Technology (IJCAT), Vol. 53, No. 1, 2016
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com