Deformable part model and deep learning comparison on victim detection Afetzede Tespitinde Deforme Edilebilir Parçali Model ve Derin Ögrenme Karsilastirmasi

ÇAKMAK F., USLU E., Altuntas N., Marangoz S., Balcilar M., AMASYALI M. F., ...More

24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Turkey, 16 - 19 May 2016, pp.1513-1516, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2016.7496039
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.1513-1516
  • Keywords: object deteciton, victim detection, deformable part model, deep learning
  • Istanbul Gelisim University Affiliated: No

Abstract

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.