Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi

Caner Gacav; Burak Benligiray; Cihan Topal

doi:10.1109/SIU.2016.7496031

Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi

Translated title of the contribution: Sequential forward feature selection for facial expression recognition

Caner Gacav, Burak Benligiray, Cihan Topal

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

9 Citations (Scopus)

Abstract

Facial expression recognition is an important computer vision problem with various applications. In this study, we investigate the effectiveness of features derived from facial landmarks in facial expression recognition. Distances between two combinations of facial landmarks constitute a distance vector. Features we use are the changes in the distance vectors extracted from expressive and neutral states of the face. The obtained feature vector contains elements that are relatively useless in expression recognition. By applying forward sequential feature selection, a subset of the most effective elements is formed. The chosen features are classified using a multi-class support vector machine. The performance of the proposed method is measured using Extended Cohn-Kanade dataset with seven expressions (anger, contempt, disgust, fear, happy, sad and surprised) and resulted in 89.9% mean class recognition accuracy.

Translated title of the contribution	Sequential forward feature selection for facial expression recognition
Original language	Turkish
Title of host publication	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1481-1484
Number of pages	4
ISBN (Electronic)	9781509016792
DOIs	https://doi.org/10.1109/SIU.2016.7496031
Publication status	Published - 20 Jun 2016
Externally published	Yes
Event	24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey Duration: 16 May 2016 → 19 May 2016

Publication series

Name	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

Conference

Conference	24th Signal Processing and Communication Application Conference, SIU 2016
Country/Territory	Turkey
City	Zonguldak
Period	16/05/16 → 19/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Access to Document

10.1109/SIU.2016.7496031

Cite this

Gacav, C., Benligiray, B., & Topal, C. (2016). Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings (pp. 1481-1484). Article 7496031 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2016.7496031

Gacav, Caner ; Benligiray, Burak ; Topal, Cihan. / Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi. 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1481-1484 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

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abstract = "Facial expression recognition is an important computer vision problem with various applications. In this study, we investigate the effectiveness of features derived from facial landmarks in facial expression recognition. Distances between two combinations of facial landmarks constitute a distance vector. Features we use are the changes in the distance vectors extracted from expressive and neutral states of the face. The obtained feature vector contains elements that are relatively useless in expression recognition. By applying forward sequential feature selection, a subset of the most effective elements is formed. The chosen features are classified using a multi-class support vector machine. The performance of the proposed method is measured using Extended Cohn-Kanade dataset with seven expressions (anger, contempt, disgust, fear, happy, sad and surprised) and resulted in 89.9% mean class recognition accuracy.",

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author = "Caner Gacav and Burak Benligiray and Cihan Topal",

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Gacav, C, Benligiray, B & Topal, C 2016, Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi. in 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings., 7496031, 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1481-1484, 24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Turkey, 16/05/16. https://doi.org/10.1109/SIU.2016.7496031

Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi. / Gacav, Caner; Benligiray, Burak; Topal, Cihan.
2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1481-1484 7496031 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

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

TY - GEN

T1 - Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi

AU - Gacav, Caner

AU - Benligiray, Burak

AU - Topal, Cihan

PY - 2016/6/20

Y1 - 2016/6/20

N2 - Facial expression recognition is an important computer vision problem with various applications. In this study, we investigate the effectiveness of features derived from facial landmarks in facial expression recognition. Distances between two combinations of facial landmarks constitute a distance vector. Features we use are the changes in the distance vectors extracted from expressive and neutral states of the face. The obtained feature vector contains elements that are relatively useless in expression recognition. By applying forward sequential feature selection, a subset of the most effective elements is formed. The chosen features are classified using a multi-class support vector machine. The performance of the proposed method is measured using Extended Cohn-Kanade dataset with seven expressions (anger, contempt, disgust, fear, happy, sad and surprised) and resulted in 89.9% mean class recognition accuracy.

AB - Facial expression recognition is an important computer vision problem with various applications. In this study, we investigate the effectiveness of features derived from facial landmarks in facial expression recognition. Distances between two combinations of facial landmarks constitute a distance vector. Features we use are the changes in the distance vectors extracted from expressive and neutral states of the face. The obtained feature vector contains elements that are relatively useless in expression recognition. By applying forward sequential feature selection, a subset of the most effective elements is formed. The chosen features are classified using a multi-class support vector machine. The performance of the proposed method is measured using Extended Cohn-Kanade dataset with seven expressions (anger, contempt, disgust, fear, happy, sad and surprised) and resulted in 89.9% mean class recognition accuracy.

KW - Cohn-Kanade dataset

KW - facial expression recognition

KW - feature selection

KW - forward sequential feature selection

KW - support vector machines

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DO - 10.1109/SIU.2016.7496031

M3 - Konferans katkısı

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T3 - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

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BT - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Gacav C, Benligiray B, Topal C. Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1481-1484. 7496031. (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). doi: 10.1109/SIU.2016.7496031

Yüz Ifadesi Tanima Için Ardisik Ileri Öznitelik Seçimi

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