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 - Jan 1 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

Fingerprint

Adaptive boosting
Set theory

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Ogata, R., Mori, M., Frinken, V., & Uchida, S. (2014). Constrained AdaBoost for Totally-Ordered Global Features. In Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 (pp. 393-398). [6981051] (Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR; Vol. 2014-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICFHR.2014.72

Constrained AdaBoost for Totally-Ordered Global Features. / Ogata, Ryota; Mori, Minoru; Frinken, Volkmar; Uchida, Seiichi.

Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 393-398 6981051 (Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR; Vol. 2014-December).

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

Ogata, R, Mori, M, Frinken, V & Uchida, S 2014, Constrained AdaBoost for Totally-Ordered Global Features. in Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014., 6981051, Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR, vol. 2014-December, Institute of Electrical and Electronics Engineers Inc., pp. 393-398, 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014, Hersonissos, Crete Island, Greece, 9/1/14. https://doi.org/10.1109/ICFHR.2014.72
Ogata R, Mori M, Frinken V, Uchida S. Constrained AdaBoost for Totally-Ordered Global Features. In Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 393-398. 6981051. (Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR). https://doi.org/10.1109/ICFHR.2014.72
Ogata, Ryota ; Mori, Minoru ; Frinken, Volkmar ; Uchida, Seiichi. / Constrained AdaBoost for Totally-Ordered Global Features. Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 393-398 (Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR).
@inproceedings{91c0a8cc818f401f95bf522528cac0e4,
title = "Constrained AdaBoost for Totally-Ordered Global Features",
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.",
author = "Ryota Ogata and Minoru Mori and Volkmar Frinken and Seiichi Uchida",
year = "2014",
month = "1",
day = "1",
doi = "10.1109/ICFHR.2014.72",
language = "English",
series = "Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "393--398",
booktitle = "Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014",
address = "United States",

}

TY - GEN

T1 - Constrained AdaBoost for Totally-Ordered Global Features

AU - Ogata, Ryota

AU - Mori, Minoru

AU - Frinken, Volkmar

AU - Uchida, Seiichi

PY - 2014/1/1

Y1 - 2014/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84942243387&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84942243387&partnerID=8YFLogxK

U2 - 10.1109/ICFHR.2014.72

DO - 10.1109/ICFHR.2014.72

M3 - Conference contribution

AN - SCOPUS:84942243387

T3 - Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR

SP - 393

EP - 398

BT - Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -