High-Resolution Navigation on Non-Differentiable Image Manifolds
| dc.citation.bibtexName | inproceedings | en_US |
| dc.citation.conferenceName | IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) | en_US |
| dc.citation.location | Philadelphia, PA | en_US |
| dc.citation.volumeNumber | 5 | en_US |
| dc.contributor.author | Wakin, Michael | en_US |
| dc.contributor.author | Donoho, David | en_US |
| dc.contributor.author | Choi, Hyeokho | en_US |
| dc.contributor.author | Baraniuk, Richard G. | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T01:09:06Z | en_US |
| dc.date.available | 2007-10-31T01:09:06Z | en_US |
| dc.date.issued | 2005-03-01 | en_US |
| dc.date.modified | 2006-06-06 | en_US |
| dc.date.note | 2005-01-21 | en_US |
| dc.date.submitted | 2005-03-01 | en_US |
| dc.description | Conference Paper | en_US |
| dc.description.abstract | The images generated by varying the underlying articulation parameters of an object (pose, attitude, light source position, and so on) can be viewed as points on a low-dimensional <i>image parameter articulation manifold</i> (IPAM) in a high-dimensional ambient space. In this paper, we develop theory and methods for the inverse problem of estimating, from a given image on or near an IPAM, the underlying parameters that produced it. Our approach is centered on the observation that, while typical image manifolds are not differentiable, they have an intrinsic multiscale geometric structure. In fact, each IPAM has a family of approximate tangent spaces, each one good at a certain resolution. Putting this structural aspect to work, we develop a new algorithm for high-accuracy parameter estimation based on a coarse-to-fine Newton iteration through the family of approximate tangent spaces. We test the algorithm in several idealized registration and pose estimation problems. | en_US |
| dc.identifier.citation | M. Wakin, D. Donoho, H. Choi and R. G. Baraniuk, "High-Resolution Navigation on Non-Differentiable Image Manifolds," vol. 5, 2005. | en_US |
| dc.identifier.doi | http://dx.doi.org/10.1109/ICASSP.2005.1416493 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/20433 | en_US |
| dc.language.iso | eng | en_US |
| dc.subject | Imaging Parameter Articulation Manifolds | en_US |
| dc.subject | Nondifferentiable Manifolds | en_US |
| dc.subject | Multiscale Registration | en_US |
| dc.subject | Pose Estimation | en_US |
| dc.subject.keyword | Imaging Parameter Articulation Manifolds | en_US |
| dc.subject.keyword | Nondifferentiable Manifolds | en_US |
| dc.subject.keyword | Multiscale Registration | en_US |
| dc.subject.keyword | Pose Estimation | en_US |
| dc.subject.other | Multiscale geometry processing | en_US |
| dc.title | High-Resolution Navigation on Non-Differentiable Image Manifolds | en_US |
| dc.type | Conference paper | en_US |
| dc.type.dcmi | Text | en_US |
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