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publ. in Proc. of the 8th Int. Workshop on Frontiers in Handwriting Recognition (IWFHR), pp. 4954, 2002. ftp://ftp.informatik.uni-freiburg.de/papers/lmb/ba_ha_bu_iwfhr02.pdf
 

Summary: publ. in Proc. of the 8th Int. Workshop on Frontiers in Handwriting Recognition (IWFHR), pp. 49­54, 2002.
ftp://ftp.informatik.uni-freiburg.de/papers/lmb/ba_ha_bu_iwfhr02.pdf
On-line Handwriting Recognition with Support Vector Machines--
A Kernel Approach
Claus Bahlmann, Bernard Haasdonk and Hans Burkhardt
Computer Science Department
Albert-Ludwigs-University Freiburg
79110 Freiburg, Germany
{bahlmann,haasdonk,burkhardt}@informatik.uni-freiburg.de
Abstract
In this contribution we describe a novel classification
approach for on-line handwriting recognition. The tech-
nique combines dynamic time warping (DTW) and sup-
port vector machines (SVMs) by establishing a new SVM
kernel. We call this kernel Gaussian DTW (GDTW) ker-
nel. This kernel approach has a main advantage over com-
mon HMM techniques. It does not assume a model for the
generative class conditional densities. Instead, it directly
addresses the problem of discrimination by creating class
boundaries and thus is less sensitive to modeling assump-

  

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

 

Collections: Computer Technologies and Information Sciences