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dc.contributor.authorWakin, Michael
Donoho, David
Choi, Hyeokho
Baraniuk, Richard G.
dc.creatorWakin, Michael
Donoho, David
Choi, Hyeokho
Baraniuk, Richard G.
dc.date.accessioned 2007-10-31T01:09:06Z
dc.date.available 2007-10-31T01:09:06Z
dc.date.issued 2005-03-01
dc.date.submitted 2005-03-01
dc.identifier.citation M. Wakin, D. Donoho, H. Choi and R. G. Baraniuk, "High-Resolution Navigation on Non-Differentiable Image Manifolds," vol. 5, 2005.
dc.identifier.urihttps://hdl.handle.net/1911/20433
dc.description Conference Paper
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 image parameter articulation manifold (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.
dc.language.iso eng
dc.subjectImaging Parameter Articulation Manifolds
Nondifferentiable Manifolds
Multiscale Registration
Pose Estimation
dc.subject.otherMultiscale geometry processing
dc.title High-Resolution Navigation on Non-Differentiable Image Manifolds
dc.type Conference paper
dc.date.note 2005-01-21
dc.citation.bibtexName inproceedings
dc.date.modified 2006-06-06
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.subject.keywordImaging Parameter Articulation Manifolds
Nondifferentiable Manifolds
Multiscale Registration
Pose Estimation
dc.citation.volumeNumber 5
dc.citation.location Philadelphia, PA
dc.citation.conferenceName IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.2005.1416493


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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1299]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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