Gender and age groups classifications for semantic annotation of videos

Yaprakkaya G., ÇİÇEKLİ F. N., ULUSOY İ.

25th International Symposium on Computer and Information Sciences, ISCIS 2010, London, İngiltere, 22 - 24 Eylül 2010, cilt.62 LNEE, ss.227-230 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 62 LNEE
  • Doi Numarası: 10.1007/978-90-481-9794-1_44
  • Basıldığı Şehir: London
  • Basıldığı Ülke: İngiltere
  • Sayfa Sayıları: ss.227-230
  • Anahtar Kelimeler: Adaboost, Age Group Classification, DCT Mod2 Features, Face Tracking, Gender Classification, LBP features, Random Forest
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This paper presents a combination of methods for gender identification and age group classification for semantic annotation of videos. The system has two different running modes as 'Training Mode' and 'Classification Mode'. The gender classifier achieves over 96% accuracy and the age group classifier achieves over 87% accuracy in age group classification. © 2011 Springer Science+Business Media B.V.