Deformable Part Model and Deep Learning Comparison on Victim Detection

Cakmak F., Uslu E., Altuntas N., Marangoz S., Balcilar M., Amasyali M. F., ...Daha Fazla

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.1513-1516 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2016.7496039
  • Basıldığı Şehir: Zonguldak
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1513-1516
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Object detection problem is a considerable research field that is being developed through continuous research. Simulated victims (dolls) detection performances of 2 different methods are given in the scope of this work. While deformable part model method is performing high accuracy and speed to detect object, with growing and remarkable popularity, deep learning method is noteworthy with higher performance results. This work mentions about the advantages and disadvantages of both methods and gives experimental results on a simulated environment.