Cilt 23, Sayı 5, Sayfalar 527 - 531

Facial expression recognition based on compressive sensing and pyramid processing
Sıkıştırılmış algılama ve piramit işlemeye dayalı yüz ifade tanıma

Alaa Eleyan [1] , Abubakar Ashir [2]

38 0

In this paper, a new approach has been proposed for improved facial expression recognition. The new approach is inspired by the compressive sensing theory and multi-resolution approach to facial expression problems. Initially, each image sample is decomposed into desired levels of its pyramids at different sizes and resolutions. At each level of the pyramid, features are extracted using a measurement matrix based on compressive sensing theory. These measurements are concatenated together to form a feature vector for the original image. The results obtained from the approach using three distance measurement classifiers (Manhattan, Euclidean, Cosine) and support vector machine are impressive and outperforms most of its counterpart algorithms in the literature using the same databases and settings.

Bu makalede, geliştirilmiş yüz ifadesi tanıma için yeni bir yaklaşım önerilmiştir. Bu yeni yaklaşım sıkıştırma algılama teorisinden ve yüz ifadesi problemine çoklu çözünürlük yaklaşımından esinlenmektedir. Başlangıçta, her bir görüntü örneği farklı boyutlarda ve çözünürlüklerdeki piramitlerin istenilen seviyesine ayrıştırılmaktadır. Piramidin her seviyesinde, özellikler sıkıştırma algılama teorisine dayanan bir ölçüm matrisi kullanılarak ayrıştırılmaktadır. Bu ölçümlerin tamamı orijinal görüntü için bir özellik vektörü oluşturmak için bir araya getirilmektedir. Üç uzaklık ölçümü sınıflandırıcısı (Manhattan, Öklid, kosinüs) ve destek vektör makinesi kullanımından elde edilen sonuçlar, aynı veri tabanları ve ayarlarının kullanıldığı literatürdeki benzer algoritmaların çoğundan daha etkileyici ve iyidir.

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Konular Mühendislik ve Temel Bilimler
Dergi Bölümü Makale
Yazarlar

Yazar: Alaa Eleyan
E-posta: aeleyan@avrasya.edu.tr

Yazar: Abubakar Ashir
E-posta: ashir4real@yahoo.com

Bibtex @araştırma makalesi { pajes345314, journal = {Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {1300-7009}, address = {Pamukkale Üniversitesi}, year = {}, volume = {23}, pages = {527 - 531}, doi = {}, title = {Facial expression recognition based on compressive sensing and pyramid processing}, language = {en}, key = {cite}, author = {Eleyan, Alaa and Ashir, Abubakar} } @araştırma makalesi { pajes345314, journal = {Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {1300-7009}, address = {Pamukkale Üniversitesi}, year = {}, volume = {23}, pages = {527 - 531}, doi = {}, title = {Sıkıştırılmış algılama ve piramit işlemeye dayalı yüz ifade tanıma}, language = {tr}, key = {cite}, author = {Eleyan, Alaa and Ashir, Abubakar} }
APA Eleyan, A , Ashir, A . (). Facial expression recognition based on compressive sensing and pyramid processing. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23 (5), 527-531. Retrieved from http://www.dergipark.gov.tr/pajes/issue/31526/345314
MLA Eleyan, A , Ashir, A . "Facial expression recognition based on compressive sensing and pyramid processing". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23 (): 527-531 <http://www.dergipark.gov.tr/pajes/issue/31526/345314>
Chicago Eleyan, A , Ashir, A . "Facial expression recognition based on compressive sensing and pyramid processing". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23 (): 527-531
RIS TY - JOUR T1 - Sıkıştırılmış algılama ve piramit işlemeye dayalı yüz ifade tanıma AU - Alaa Eleyan , Abubakar Ashir Y1 - 2018 PY - 2018 N1 - DO - T2 - Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi JF - Journal JO - JOR SP - 527 EP - 531 VL - 23 IS - 5 SN - 1300-7009-2147-5881 M3 - UR - Y2 - 2018 ER -
EndNote %0 Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi Sıkıştırılmış algılama ve piramit işlemeye dayalı yüz ifade tanıma %A Alaa Eleyan , Abubakar Ashir %T Sıkıştırılmış algılama ve piramit işlemeye dayalı yüz ifade tanıma %D 2018 %J Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi %P 1300-7009-2147-5881 %V 23 %N 5 %R %U