Research

Optical flow estimation using Laplacian Mesh Energy


Reference:

Li, W., Cosker, D., Brown, M. and Tang, R., 2013. Optical flow estimation using Laplacian Mesh Energy. In: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2013-06-25 - 2013-06-27.

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Official URL:

http://dx.doi.org/10.1109/CVPR.2013.315

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Abstract

In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration. The algorithm uses a unique Laplacian Mesh Energy term to encourage local smoothness whilst simultaneously preserving non-rigid deformation. Laplacian deformation approaches have become popular in graphics research as they enable mesh deformations to preserve local surface shape. In this work we propose a novel Laplacian Mesh Energy formula to ensure such sensible local deformations between image pairs. We express this wholly within the optical flow optimization, and show its application in a novel coarse-to-fine pyramidal approach. Our algorithm achieves the state-of-the-art performance in all trials on the Garg et al. dataset, and top tier performance on the Middlebury evaluation.

Details

Item Type Conference or Workshop Items (Paper)
CreatorsLi, W., Cosker, D., Brown, M. and Tang, R.
DOI10.1109/CVPR.2013.315
Related URLs
URLURL Type
http://www.cv-foundation.org/openaccess/CVPR2013.pyFree Full-text
DepartmentsFaculty of Science > Computer Science
Research CentresMedia Technology Research Centre
Publisher StatementLME_CamReady.pdf: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
RefereedYes
StatusPublished
ID Code34534

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