Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

6-2012

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 canonically 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.

Discipline

Graphics and Human Computer Interfaces | Programming Languages and Compilers

Research Areas

Data Science and Engineering

Publication

Proceedings of the 25th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012, Providence, Providence, United States, June 16-21

First Page

1

Last Page

8

ISBN

9781467312264

Identifier

10.1109/CVPR.2012.6247651

Publisher

IEEE

City or Country

Providence, United States

Additional URL

https://doi.org/10.1109/CVPR.2012.6247651

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