Constrained AdaBoost for Totally-Ordered Global Features

Ryota Ogata, Minoru Mori, Volkmar Frinken, Seiichi Uchida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a constrained AdaBoost algorithm for utilizing global features in a dynamic time warping (DTW) framework. Global features are defined as a spatial relationship between temporally-distant points of a temporal pattern and are useful to represent global structure of the pattern. An example is the spatial relationship between the first and the last points of a handwritten pattern of the digit '0'. Those temporally-distant points should be spatially close enough to form a closed circle, whereas those points of '6' should be distant enough. For a temporal pattern of an N-point sequence, it is possible to have N(N - 1)/2 global features. One problem of using the global features is that they are not ordered as a one dimensional sequence any more. Consequently, it is impossible to use them in a left-to-right Markovian model, such as DTW and HMM. The proposed constrained AdaBoost algorithm can select a totally-ordered subset from the set of N(N - 1)/2 global features. Since the totally-ordered features can be arranged as a one-dimensional sequence, they can be incorporated into a DTW framework for compensating nonlinear temporal fluctuation. Since the selection is governed by the AdaBoost framework, the selected features can retain discriminative power.

Original languageEnglish
Title of host publicationProceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages393-398
Number of pages6
ISBN (Electronic)9781479943340
DOIs
Publication statusPublished - Dec 9 2014
Event14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 - Hersonissos, Crete Island, Greece
Duration: Sep 1 2014Sep 4 2014

Publication series

NameProceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Volume2014-December
ISSN (Print)2167-6445
ISSN (Electronic)2167-6453

Other

Other14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014
CountryGreece
CityHersonissos, Crete Island
Period9/1/149/4/14

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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