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Adaptive vs. Non-Adaptive Strategies for the Computation of Optical Flow

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Condell, JV, Scotney, BW and Morrow, PJ (2006) Adaptive vs. Non-Adaptive Strategies for the Computation of Optical Flow. International Journal of Imaging Systems and Technology, 16 (2). pp. 35-50. [Journal article]

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DOI: 10.1002/ima.20066

Abstract

Confident adaptive algorithms are described, evaluated,and compared with other algorithms that implement the estimationof motion. A Galerkin finite element adaptive approach isdescribed for computing optical flow, which uses an adaptive triangularmesh in which the resolution increases where motion is found tooccur. The mesh facilitates a reduction in computational effort by enablingprocessing to focus on particular objects of interest in a scene.Compared with other state-of-the-art methods in the literature ouradaptive methods show only motion where main movement is knownto occur, indicating a methodological improvement. The mesh refinement,based on detected motion, gives an alternative to methodsreported in the literature, where the adaptation is usually based on agradient intensity measure. A confidence is calculated for the detectedmotion and if this measure passes the threshold then themotion is used in the adaptive mesh refinement process. The idea ofusing the reliability hypothesis test is straightforward. The incorporationof the confidence serves the purpose of increasing the opticalflow determination reliability. Generally, the confident flow seemsmost consistent, accurate and efficient, and focuses on the mainmoving objects within the image.

Item Type:Journal article
Keywords:adaptive grids; confidence measures; finite element methods; optical flow
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:34
Deposited By:Dr Joan Condell
Deposited On:10 Aug 2009 10:11
Last Modified:15 Jun 2011 11:07

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