Greedy search for descriptive spatial face features

Caner Gacav; Burak Benligiray; Cihan Topal

doi:10.1109/ICASSP.2017.7952406

Greedy search for descriptive spatial face features

Caner Gacav, Burak Benligiray, Cihan Topal

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

5 Atıf (Scopus)

Özet

Facial expression recognition methods use a combination of geometric and appearance-based features. Spatial features are derived from displacements of facial landmarks, and carry geometric information. These features are either selected based on prior knowledge, or dimension-reduced from a large pool. In this study, we produce a large number of potential spatial features using two combinations of facial landmarks. Among these, we search for a descriptive subset of features using sequential forward selection. The chosen feature subset is used to classify facial expressions in the extended Cohn-Kanade dataset (CK+), and delivered 88.7% recognition accuracy without using any appearance-based features.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1497-1501
Sayfa sayısı	5
ISBN (Elektronik)	9781509041176
DOI'lar	https://doi.org/10.1109/ICASSP.2017.7952406
Yayın durumu	Yayınlandı - 16 Haz 2017
Harici olarak yayınlandı	Evet
Etkinlik	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States Süre: 5 Mar 2017 → 9 Mar 2017

Yayın serisi

Adı	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Basılı)	1520-6149

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Ülke/Bölge	United States
Şehir	New Orleans
Periyot	5/03/17 → 9/03/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Belgeye Erişim

10.1109/ICASSP.2017.7952406

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Gacav, C., Benligiray, B., & Topal, C. (2017). Greedy search for descriptive spatial face features. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 1497-1501). Makale 7952406 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2017.7952406

Gacav, Caner ; Benligiray, Burak ; Topal, Cihan. / Greedy search for descriptive spatial face features. 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1497-1501 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

@inproceedings{107b1b16667e4d498af9c431c45c34ef,

title = "Greedy search for descriptive spatial face features",

abstract = "Facial expression recognition methods use a combination of geometric and appearance-based features. Spatial features are derived from displacements of facial landmarks, and carry geometric information. These features are either selected based on prior knowledge, or dimension-reduced from a large pool. In this study, we produce a large number of potential spatial features using two combinations of facial landmarks. Among these, we search for a descriptive subset of features using sequential forward selection. The chosen feature subset is used to classify facial expressions in the extended Cohn-Kanade dataset (CK+), and delivered 88.7% recognition accuracy without using any appearance-based features.",

keywords = "facial expression recognition, sequential forward selection, spatial features",

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

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",

year = "2017",

month = jun,

day = "16",

doi = "10.1109/ICASSP.2017.7952406",

language = "English",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1497--1501",

booktitle = "2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings",

address = "United States",

}

Gacav, C, Benligiray, B & Topal, C 2017, Greedy search for descriptive spatial face features. in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings., 7952406, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1497-1501, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017, New Orleans, United States, 5/03/17. https://doi.org/10.1109/ICASSP.2017.7952406

Greedy search for descriptive spatial face features. / Gacav, Caner; Benligiray, Burak; Topal, Cihan.
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1497-1501 7952406 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Greedy search for descriptive spatial face features

AU - Gacav, Caner

AU - Benligiray, Burak

AU - Topal, Cihan

PY - 2017/6/16

Y1 - 2017/6/16

N2 - Facial expression recognition methods use a combination of geometric and appearance-based features. Spatial features are derived from displacements of facial landmarks, and carry geometric information. These features are either selected based on prior knowledge, or dimension-reduced from a large pool. In this study, we produce a large number of potential spatial features using two combinations of facial landmarks. Among these, we search for a descriptive subset of features using sequential forward selection. The chosen feature subset is used to classify facial expressions in the extended Cohn-Kanade dataset (CK+), and delivered 88.7% recognition accuracy without using any appearance-based features.

AB - Facial expression recognition methods use a combination of geometric and appearance-based features. Spatial features are derived from displacements of facial landmarks, and carry geometric information. These features are either selected based on prior knowledge, or dimension-reduced from a large pool. In this study, we produce a large number of potential spatial features using two combinations of facial landmarks. Among these, we search for a descriptive subset of features using sequential forward selection. The chosen feature subset is used to classify facial expressions in the extended Cohn-Kanade dataset (CK+), and delivered 88.7% recognition accuracy without using any appearance-based features.

KW - facial expression recognition

KW - sequential forward selection

KW - spatial features

UR - http://www.scopus.com/inward/record.url?scp=85023772415&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2017.7952406

DO - 10.1109/ICASSP.2017.7952406

M3 - Conference contribution

AN - SCOPUS:85023772415

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - 1497

EP - 1501

BT - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017

Y2 - 5 March 2017 through 9 March 2017

ER -

Gacav C, Benligiray B, Topal C. Greedy search for descriptive spatial face features. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1497-1501. 7952406. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2017.7952406

Greedy search for descriptive spatial face features

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap