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|Title:||Aligning images in the wild|
|Citation:||Lin, W.-Y.,Liu, L.,Matsushita, Y.,Low, K.-L.,Liu, S. (2012). Aligning images in the wild. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition : 1-8. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPR.2012.6247651|
|Abstract:||Aligning image pairs with significant appearance change is a long standing computer vision challenge. Much of this problem stems from the local patch descriptors' instability to appearance variation. In this paper we suggest this instability is due less to descriptor corruption and more the difficulty in utilizing local information to canoni-cally define the orientation (scale and rotation) at which a patch's descriptor should be computed. We address this issue by jointly estimating correspondence and relative patch orientation, within a hierarchical algorithm that utilizes a smoothly varying parameterization of geometric transformations. By collectively estimating the correspondence and orientation of all the features, we can align and orient features that cannot be stably matched with only local information. At the price of smoothing over motion discontinuities (due to independent motion or parallax), this approach can align image pairs that display significant inter-image appearance variations. © 2012 IEEE.|
|Source Title:||Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|Appears in Collections:||Staff Publications|
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