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Sıkıştırılmış algılama ve piramit işlemeye dayalı yüz ifade tanıma

Facial expression recognition based on compressive sensing and pyramid processing

Journal Name:

  • Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi

Publication Year:

  • 2017
DOI: 
10.5505/pajes.2016.43402

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
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.
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Abstract (Original Language): 
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.
FULL TEXT (PDF): 
PDF icon arastirmax-sikistirilmis-algilama-piramit-islemeye-dayali-yuz-ifade-tanima.pdf
  • 5
527
531
  • Turkish

REFERENCES

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