Kernel Canonical Correlation Analysis (bibtex)
by Thomas Melzer, Michael Reiter, Horst Bischof
Abstract:
This paper introduces a new non-linear feature extraction technique based on \emphCanonical Correlation Analysis (CCA) with applications in regression and object recognition. The non-linear transformation of the input data is performed using kernel-methods. Although, in this respect, our approach is similar to other \emphgeneralized linear methods like kernel-PCA, our method is especially well suited for relating two sets of measurements. The benefits of our method compared to standard feature extraction methods based on PCA will be illustrated with several experiments from the field of object recognition and pose estimation.
Reference:
Kernel Canonical Correlation Analysis (Thomas Melzer, Michael Reiter, Horst Bischof), Technical report, PRIP, TU Wien, 2001.
Bibtex Entry:
@TechReport{TR065,
  author =	 "Thomas Melzer and Michael Reiter and Horst Bischof",
  institution =	 "PRIP, TU Wien",
  number =	 "PRIP-TR-065",
  title =	 "Kernel {C}anonical {C}orrelation {A}nalysis",
  year =	 "2001",
  url =		 "ftp://ftp.prip.tuwien.ac.at/pub/publications/trs/tr65.pdf",
  abstract =	 "This paper introduces a new non-linear feature
                  extraction technique based on \emph{Canonical
                  Correlation Analysis} (CCA) with applications in
                  regression and object recognition. The non-linear
                  transformation of the input data is performed using
                  kernel-methods. Although, in this respect, our
                  approach is similar to other \emph{generalized}
                  linear methods like kernel-PCA, our method is
                  especially well suited for relating two sets of
                  measurements. The benefits of our method compared to
                  standard feature extraction methods based on PCA
                  will be illustrated with several experiments from
                  the field of object recognition and pose
                  estimation.",
}
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