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ACCV
2007
Springer

Interpolation Between Eigenspaces Using Rotation in Multiple Dimensions

10 years 1 months ago
Interpolation Between Eigenspaces Using Rotation in Multiple Dimensions
We propose a method for interpolation between eigenspaces. Techniques that represent observed patterns as multivariate normal distribution have actively been developed to make it robust over observation noises. In the recognition of images that vary based on continuous parameters such as camera angles, one cause that degrades performance is training images that are observed discretely while the parameters are varied continuously. The proposed method interpolates between eigenspaces by analogy from rotation of a hyper-ellipsoid in high dimensional space. Experiments using face images captured in various illumination conditions demonstrate the validity and effectiveness of the proposed interpolation method.
Tomokazu Takahashi, Lina, Ichiro Ide, Yoshito Meka
Added 06 Jun 2010
Updated 06 Jun 2010
Type Conference
Year 2007
Where ACCV
Authors Tomokazu Takahashi, Lina, Ichiro Ide, Yoshito Mekada, Hiroshi Murase
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