Emotion recognition: The influence of texture’s descriptors on classification accuracy

Karolina Nurzynska

doi:10.1007/978-3-319-58274-0_34

Emotion recognition: The influence of texture’s descriptors on classification accuracy

Karolina Nurzynska

Department of Algorithmics and Software (RAU/RAU5)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

This work describes experiments dedicated to analysis of the descriptive properties of several, most widely applied, texture operators in emotion recognition domain. Many researchers apply Gabor filters, histogram of oriented gradients, or local binary patterns in complex set-ups with different classification approaches and image processing methodologies, but nowhere it was verified, how each part of the system influences the resulting performance. Therefore, several experiments with Cohn-Kanade AU-Coded Facial Expression and Karolinska Directed Emotional Faces Databases were performed. These experiments reviled, that exploiting the histogram of oriented gradients overcomes other texture operators in most cases.

Original language	English
Title of host publication	Beyond Databases, Architectures and Structures
Subtitle of host publication	Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings
Editors	Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bozena Malysiak-Mrozek, Daniel Kostrzewa
Publisher	Springer Verlag
Pages	427-438
Number of pages	12
ISBN (Print)	9783319582733
DOIs	https://doi.org/10.1007/978-3-319-58274-0_34
Publication status	Published - 2017
Event	13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017 - Ustron, Poland Duration: 30 May 2017 → 2 Jun 2017

Publication series

Name	Communications in Computer and Information Science
Volume	716
ISSN (Print)	1865-0929

Conference

Conference	13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017
Country/Territory	Poland
City	Ustron
Period	30/05/17 → 2/06/17

Keywords

Classification
Emotion recognition
Gabor filters
Histogram of oriented gradients
Local binary patterns
Texture operators

ASJC Scopus subject areas

General Computer Science
General Mathematics

Access to Document

10.1007/978-3-319-58274-0_34

Cite this

Nurzynska, K. (2017). Emotion recognition: The influence of texture’s descriptors on classification accuracy. In S. Kozielski, D. Mrozek, P. Kasprowski, B. Malysiak-Mrozek, & D. Kostrzewa (Eds.), Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings (pp. 427-438). (Communications in Computer and Information Science; Vol. 716). Springer Verlag. https://doi.org/10.1007/978-3-319-58274-0_34

Nurzynska, Karolina. / Emotion recognition : The influence of texture’s descriptors on classification accuracy. Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. editor / Stanislaw Kozielski ; Dariusz Mrozek ; Pawel Kasprowski ; Bozena Malysiak-Mrozek ; Daniel Kostrzewa. Springer Verlag, 2017. pp. 427-438 (Communications in Computer and Information Science).

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title = "Emotion recognition: The influence of texture{\textquoteright}s descriptors on classification accuracy",

abstract = "This work describes experiments dedicated to analysis of the descriptive properties of several, most widely applied, texture operators in emotion recognition domain. Many researchers apply Gabor filters, histogram of oriented gradients, or local binary patterns in complex set-ups with different classification approaches and image processing methodologies, but nowhere it was verified, how each part of the system influences the resulting performance. Therefore, several experiments with Cohn-Kanade AU-Coded Facial Expression and Karolinska Directed Emotional Faces Databases were performed. These experiments reviled, that exploiting the histogram of oriented gradients overcomes other texture operators in most cases.",

keywords = "Classification, Emotion recognition, Gabor filters, Histogram of oriented gradients, Local binary patterns, Texture operators",

author = "Karolina Nurzynska",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017 ; Conference date: 30-05-2017 Through 02-06-2017",

year = "2017",

doi = "10.1007/978-3-319-58274-0\_34",

language = "English",

isbn = "9783319582733",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "427--438",

editor = "Stanislaw Kozielski and Dariusz Mrozek and Pawel Kasprowski and Bozena Malysiak-Mrozek and Daniel Kostrzewa",

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Nurzynska, K 2017, Emotion recognition: The influence of texture’s descriptors on classification accuracy. in S Kozielski, D Mrozek, P Kasprowski, B Malysiak-Mrozek & D Kostrzewa (eds), Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. Communications in Computer and Information Science, vol. 716, Springer Verlag, pp. 427-438, 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017, Ustron, Poland, 30/05/17. https://doi.org/10.1007/978-3-319-58274-0_34

Emotion recognition: The influence of texture’s descriptors on classification accuracy. / Nurzynska, Karolina.
Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. ed. / Stanislaw Kozielski; Dariusz Mrozek; Pawel Kasprowski; Bozena Malysiak-Mrozek; Daniel Kostrzewa. Springer Verlag, 2017. p. 427-438 (Communications in Computer and Information Science; Vol. 716).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Emotion recognition

T2 - 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017

AU - Nurzynska, Karolina

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - This work describes experiments dedicated to analysis of the descriptive properties of several, most widely applied, texture operators in emotion recognition domain. Many researchers apply Gabor filters, histogram of oriented gradients, or local binary patterns in complex set-ups with different classification approaches and image processing methodologies, but nowhere it was verified, how each part of the system influences the resulting performance. Therefore, several experiments with Cohn-Kanade AU-Coded Facial Expression and Karolinska Directed Emotional Faces Databases were performed. These experiments reviled, that exploiting the histogram of oriented gradients overcomes other texture operators in most cases.

AB - This work describes experiments dedicated to analysis of the descriptive properties of several, most widely applied, texture operators in emotion recognition domain. Many researchers apply Gabor filters, histogram of oriented gradients, or local binary patterns in complex set-ups with different classification approaches and image processing methodologies, but nowhere it was verified, how each part of the system influences the resulting performance. Therefore, several experiments with Cohn-Kanade AU-Coded Facial Expression and Karolinska Directed Emotional Faces Databases were performed. These experiments reviled, that exploiting the histogram of oriented gradients overcomes other texture operators in most cases.

KW - Classification

KW - Emotion recognition

KW - Gabor filters

KW - Histogram of oriented gradients

KW - Local binary patterns

KW - Texture operators

UR - https://www.scopus.com/pages/publications/85019709797

U2 - 10.1007/978-3-319-58274-0_34

DO - 10.1007/978-3-319-58274-0_34

M3 - Conference contribution

AN - SCOPUS:85019709797

SN - 9783319582733

T3 - Communications in Computer and Information Science

SP - 427

EP - 438

BT - Beyond Databases, Architectures and Structures

A2 - Kozielski, Stanislaw

A2 - Mrozek, Dariusz

A2 - Kasprowski, Pawel

A2 - Malysiak-Mrozek, Bozena

A2 - Kostrzewa, Daniel

PB - Springer Verlag

Y2 - 30 May 2017 through 2 June 2017

ER -

Nurzynska K. Emotion recognition: The influence of texture’s descriptors on classification accuracy. In Kozielski S, Mrozek D, Kasprowski P, Malysiak-Mrozek B, Kostrzewa D, editors, Beyond Databases, Architectures and Structures: Towards Efficient Solutions for Data Analysis and Knowledge Representation - 13th International Conference, BDAS 2017, Proceedings. Springer Verlag. 2017. p. 427-438. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-58274-0_34

Emotion recognition: The influence of texture’s descriptors on classification accuracy

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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