Analysis of the effect of image resolution on automatic face gender and age classification Görüntü Çözünürlüǧünün Otomatik Cinsiyet ve Yaş Siniflandirmasindaki Etkisinin Analizi
24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.853-856, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/siu.2016.7495874
- Basıldığı Şehir: Zonguldak
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.853-856
- Anahtar Kelimeler: Age Classification, Gender Classification, k-Nearest Neighbor (k-NN), Random Forests (RF), Support Vector Machines (SVM)
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Hayır
Özet
© 2016 IEEE.In this paper, the effect of the image resolution for gender detection and age classification have been analyzed by conducting experiments with facial images that have 10 different image resolutions ranging from 2 × 1 to 329 × 264. K Nearest Neighbor (k-NN), Support Vector Machine (SVM) and Random Forests (RF) classifiers, which have been successfully used in several applications, have been employed to extract gender and age information from the images. Experiments for age classification and gender detection have been performed separately.