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| Data-Driven Motion Estimation With Spatial Adaptation
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Full
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Download
Complete Issue PDF(2.27MB) |
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Volume: 6 Issue: 1 |
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Pages: NULL |
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Publication
Date: February 2012 |
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ISSN
(Online): 1985-2304 |
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Pages |
54 - 67 |
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Author(s) |
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Published
Date |
21-02-2012 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Motion Estimation, Cross-Validation, Regularization, Inverse Problems in Image Processing, Model validation |
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| The pel-recursive computation of 2-D optical flow raises a wealth of issues, such as the treatment of outliers, motion discontinuities and occlusion. Our proposed approach deals with these issues within a common framework. It relies on the use of a data-driven technique called Generalised Cross Validation to estimate the best regularisation scheme for a given pixel. In our model, the regularisation parameter is a general matrix whose entries can account for different sources of error. The motion vector estimation takes into consideration local image properties following a spatially adaptive approach where each moving pixel is supposed to have its own regularisation matrix. Preliminary experiments indicate that this approach provides robust estimates of the optical flow. |
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| Alessandra Martins Coelho : Colleagues
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| Vania Vieira Estrela : Colleagues
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