Re-thinking non-rigid structure from motion
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Re-thinking non-rigid structure from motion. / Rabaud, Vincent; Belongie, Serge.
In: 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.Research output: Contribution to journal › Conference article › Research › peer-review
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TY - GEN
T1 - Re-thinking non-rigid structure from motion
AU - Rabaud, Vincent
AU - Belongie, Serge
PY - 2008
Y1 - 2008
N2 - We present a novel approach to non-rigid structure from motion (NRSFM) from an orthographic video sequence, based on a new interpretation of the problem. Existing approaches assume the object shape space is well-modeled by a linear subspace. Our approach only assumes that small neighborhoods of shapes are well-modeled with a linear subspace. This constrains the shapes to belong to a manifold of dimensionality equal to the number of degrees of freedom of the object. After showing that the problem is still overconstrained, we present a solution composed of a novel initialization algorithm, followed by a robust extension of the Locally Smooth Manifold Learning algorithm tailored to the NRSFM problem. We finally present some test cases where the linear basis method fails (and is actually not meant to work) while the proposed approach is successful.
AB - We present a novel approach to non-rigid structure from motion (NRSFM) from an orthographic video sequence, based on a new interpretation of the problem. Existing approaches assume the object shape space is well-modeled by a linear subspace. Our approach only assumes that small neighborhoods of shapes are well-modeled with a linear subspace. This constrains the shapes to belong to a manifold of dimensionality equal to the number of degrees of freedom of the object. After showing that the problem is still overconstrained, we present a solution composed of a novel initialization algorithm, followed by a robust extension of the Locally Smooth Manifold Learning algorithm tailored to the NRSFM problem. We finally present some test cases where the linear basis method fails (and is actually not meant to work) while the proposed approach is successful.
UR - http://www.scopus.com/inward/record.url?scp=51949102217&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2008.4587679
DO - 10.1109/CVPR.2008.4587679
M3 - Conference article
AN - SCOPUS:51949102217
JO - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
JF - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
T2 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Y2 - 23 June 2008 through 28 June 2008
ER -
ID: 302050887