Merging linear discriminant analysis with Bag of Words model for human action recognition

Alexandros Iosifidis; Anastasios Tefas; Ioannis Pitas

doi:10.1109/ICIP.2015.7350916

Merging linear discriminant analysis with Bag of Words model for human action recognition

Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

5 Citations (Scopus)

331 Downloads (Pure)

Abstract

In this paper we propose a novel method for human action recognition, that unifies discriminative Bag of Words (BoW)-based video representation and discriminant subspace learning. An iterative optimization scheme is proposed for sequential discriminant BoWs-based action representation and codebook adaptation based on action discrimination in a reduced dimensionality feature space where action classes are better discriminated. Experiments on four publicly available action recognition data sets demonstrate that the proposed unified approach increases the discriminative ability of the obtained video representation, providing enhanced action classification performance.

Original language	English
Title of host publication	2015 IEEE International Conference on Image Processing (ICIP 2015)
Subtitle of host publication	Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	832-836
Number of pages	5
ISBN (Electronic)	9781479983391
ISBN (Print)	9781479983407
DOIs	https://doi.org/10.1109/ICIP.2015.7350916
Publication status	Published - Jan 2016
Event	2015 IEEE International Conference on Image Processing (ICIP) - Quebec City, ON, Canada Duration: 27 Sept 2015 → 30 Sept 2015

Conference

Conference	2015 IEEE International Conference on Image Processing (ICIP)
Country/Territory	Canada
City	Quebec City, ON
Period	27/09/15 → 30/09/15

Keywords

Bag of Words
Discriminant Learning

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10.1109/ICIP.2015.7350916

Ioannis Pitas - Merging linear discriminant analysis with bag of words model for human action recognition - 2015Accepted author manuscript, 209 KB

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Iosifidis, A., Tefas, A., & Pitas, I. (2016). Merging linear discriminant analysis with Bag of Words model for human action recognition. In 2015 IEEE International Conference on Image Processing (ICIP 2015): Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada (pp. 832-836). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICIP.2015.7350916

Iosifidis, Alexandros ; Tefas, Anastasios ; Pitas, Ioannis. / Merging linear discriminant analysis with Bag of Words model for human action recognition. 2015 IEEE International Conference on Image Processing (ICIP 2015): Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada. Institute of Electrical and Electronics Engineers (IEEE), 2016. pp. 832-836

@inproceedings{a1bfa3817acd44a08ca305002d242fcf,

title = "Merging linear discriminant analysis with Bag of Words model for human action recognition",

abstract = "In this paper we propose a novel method for human action recognition, that unifies discriminative Bag of Words (BoW)-based video representation and discriminant subspace learning. An iterative optimization scheme is proposed for sequential discriminant BoWs-based action representation and codebook adaptation based on action discrimination in a reduced dimensionality feature space where action classes are better discriminated. Experiments on four publicly available action recognition data sets demonstrate that the proposed unified approach increases the discriminative ability of the obtained video representation, providing enhanced action classification performance.",

keywords = "Bag of Words, Discriminant Learning",

author = "Alexandros Iosifidis and Anastasios Tefas and Ioannis Pitas",

year = "2016",

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language = "English",

isbn = "9781479983407",

pages = "832--836",

booktitle = "2015 IEEE International Conference on Image Processing (ICIP 2015)",

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note = "2015 IEEE International Conference on Image Processing (ICIP) ; Conference date: 27-09-2015 Through 30-09-2015",

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Iosifidis, A, Tefas, A & Pitas, I 2016, Merging linear discriminant analysis with Bag of Words model for human action recognition. in 2015 IEEE International Conference on Image Processing (ICIP 2015): Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada. Institute of Electrical and Electronics Engineers (IEEE), pp. 832-836, 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, ON, Canada, 27/09/15. https://doi.org/10.1109/ICIP.2015.7350916

Merging linear discriminant analysis with Bag of Words model for human action recognition. / Iosifidis, Alexandros; Tefas, Anastasios; Pitas, Ioannis.
2015 IEEE International Conference on Image Processing (ICIP 2015): Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada. Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 832-836.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Merging linear discriminant analysis with Bag of Words model for human action recognition

AU - Iosifidis, Alexandros

AU - Tefas, Anastasios

AU - Pitas, Ioannis

PY - 2016/1

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N2 - In this paper we propose a novel method for human action recognition, that unifies discriminative Bag of Words (BoW)-based video representation and discriminant subspace learning. An iterative optimization scheme is proposed for sequential discriminant BoWs-based action representation and codebook adaptation based on action discrimination in a reduced dimensionality feature space where action classes are better discriminated. Experiments on four publicly available action recognition data sets demonstrate that the proposed unified approach increases the discriminative ability of the obtained video representation, providing enhanced action classification performance.

AB - In this paper we propose a novel method for human action recognition, that unifies discriminative Bag of Words (BoW)-based video representation and discriminant subspace learning. An iterative optimization scheme is proposed for sequential discriminant BoWs-based action representation and codebook adaptation based on action discrimination in a reduced dimensionality feature space where action classes are better discriminated. Experiments on four publicly available action recognition data sets demonstrate that the proposed unified approach increases the discriminative ability of the obtained video representation, providing enhanced action classification performance.

KW - Bag of Words

KW - Discriminant Learning

U2 - 10.1109/ICIP.2015.7350916

DO - 10.1109/ICIP.2015.7350916

M3 - Conference Contribution (Conference Proceeding)

SN - 9781479983407

SP - 832

EP - 836

BT - 2015 IEEE International Conference on Image Processing (ICIP 2015)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2015 IEEE International Conference on Image Processing (ICIP)

Y2 - 27 September 2015 through 30 September 2015

ER -

Iosifidis A, Tefas A, Pitas I. Merging linear discriminant analysis with Bag of Words model for human action recognition. In 2015 IEEE International Conference on Image Processing (ICIP 2015): Proceedings of a meeting held 27-30 September 2015, Quebec City, Quebec, Canada. Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 832-836 Epub 2015 Sept 27. doi: 10.1109/ICIP.2015.7350916

Merging linear discriminant analysis with Bag of Words model for human action recognition

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