article

A conditional random field-based model for joint sequence segmentation and classification

Authors:

Sotirios P. Chatzis,

Dimitrios I. Kosmopoulos,

Paul DoliotisAuthors Info & Claims

Pattern Recognition, Volume 46, Issue 6

Pages 1569 - 1578

https://doi.org/10.1016/j.patcog.2012.11.028

Published: 01 June 2013 Publication History

Abstract

In this paper, we consider the problem of joint segmentation and classification of sequences in the framework of conditional random field (CRF) models. To effect this goal, we introduce a novel dual-functionality CRF model: on the first level, the proposed model conducts sequence segmentation, whereas, on the second level, the whole observed sequences are classified into one of the available learned classes. These two procedures are conducted in a joint, synergetic fashion, thus optimally exploiting the information contained in the used model training sequences. Model training is conducted by means of an efficient likelihood maximization algorithm, and inference is based on the familiar Viterbi algorithm. We evaluate the efficacy of our approach considering a real-world application, and we compare its performance to popular alternatives.

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Cited By

Kosmopoulos DPapoutsakis KArgyros A(2017)A Framework for Online Segmentation and Classification of Modeled Actions Performed in the Context of Unmodeled OnesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2016.258967827:12(2578-2590)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1109/TCSVT.2016.2589678
Shinmoto Torres RShi Qvan den Hengel ARanasinghe D(2017)A hierarchical model for recognizing alarming states in a batteryless sensor alarm intervention for preventing falls in older peoplePervasive and Mobile Computing10.1016/j.pmcj.2017.04.00240:C(1-16)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.pmcj.2017.04.002
Zhang PLi MWu YAn LJia L(2016)Unsupervised SAR image segmentation using high-order conditional random fields model based on product-of-expertsPattern Recognition Letters10.1016/j.patrec.2016.03.03278:C(48-55)Online publication date: 15-Jul-2016
https://dl.acm.org/doi/10.1016/j.patrec.2016.03.032
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A conditional random field-based model for joint sequence segmentation and classification
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Published In

cover image Pattern Recognition

Pattern Recognition Volume 46, Issue 6

June, 2013

225 pages

ISSN:0031-3203

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Copyright © Elsevier Ltd © 2012.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 June 2013

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Cited By

Kosmopoulos DPapoutsakis KArgyros A(2017)A Framework for Online Segmentation and Classification of Modeled Actions Performed in the Context of Unmodeled OnesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2016.258967827:12(2578-2590)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1109/TCSVT.2016.2589678
Shinmoto Torres RShi Qvan den Hengel ARanasinghe D(2017)A hierarchical model for recognizing alarming states in a batteryless sensor alarm intervention for preventing falls in older peoplePervasive and Mobile Computing10.1016/j.pmcj.2017.04.00240:C(1-16)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.pmcj.2017.04.002
Zhang PLi MWu YAn LJia L(2016)Unsupervised SAR image segmentation using high-order conditional random fields model based on product-of-expertsPattern Recognition Letters10.1016/j.patrec.2016.03.03278:C(48-55)Online publication date: 15-Jul-2016
https://dl.acm.org/doi/10.1016/j.patrec.2016.03.032
Kosmopoulos DMaglogiannis IMakedon FMariottini GKorn OMaglogiannis IMetsis V(2015)Joint segmentation and classification of actions using a conditional random fieldProceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments10.1145/2769493.2769586(1-4)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1145/2769493.2769586
Fei FYang YXu WYang Y(2015)An Effective Resolution Method of Chinese Multi-category Words with Conditional Random Field in Electronic CommerceProceeings, Part II, of the 22nd International Conference on Neural Information Processing - Volume 949010.1007/978-3-319-26535-3_64(562-570)Online publication date: 9-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-26535-3_64
Jiang XZhong FPeng QQin X(2014)Online robust action recognition based on a hierarchical modelThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-014-0923-830:9(1021-1033)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1007/s00371-014-0923-8

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