TY - GEN
T1 - Finding minimal parameterizations of cylindrical image manifolds
AU - Dixon, Michael
AU - Jacobs, Nathan
AU - Pless, Robert
PY - 2006
Y1 - 2006
N2 - Manifold learning has become an important tool to characterize high-dimensional data that vary nonlinearly due to a few parameters. Applications to the analysis of medical imagery and human motion patterns have been successful despite the lack of effective tools to parameterize cyclic data sets. This paper offers an initial approach to this problem, and provides for a minimal parameterization of points that are drawn from cylindrical manifolds - data whose (unknown) generative model includes a cyclic and a non-cyclic parameter. Solving for this special case is important for a number of current, practical applications and provides a start toward a general approach to cyclic manifolds. We offer results on synthetic and real data sets and illustrate an application to de-noising cardiac ultrasound images.
AB - Manifold learning has become an important tool to characterize high-dimensional data that vary nonlinearly due to a few parameters. Applications to the analysis of medical imagery and human motion patterns have been successful despite the lack of effective tools to parameterize cyclic data sets. This paper offers an initial approach to this problem, and provides for a minimal parameterization of points that are drawn from cylindrical manifolds - data whose (unknown) generative model includes a cyclic and a non-cyclic parameter. Solving for this special case is important for a number of current, practical applications and provides a start toward a general approach to cyclic manifolds. We offer results on synthetic and real data sets and illustrate an application to de-noising cardiac ultrasound images.
UR - http://www.scopus.com/inward/record.url?scp=33845546913&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33845546913&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2006.82
DO - 10.1109/CVPRW.2006.82
M3 - Conference contribution
AN - SCOPUS:33845546913
SN - 0769526462
SN - 9780769526461
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
BT - 2006 Conference on Computer Vision and Pattern Recognition Workshop
T2 - 2006 Conference on Computer Vision and Pattern Recognition Workshops
Y2 - 17 June 2006 through 22 June 2006
ER -