Pedestrian Detection with an Improved Adaboost

Tetik Y. E., BOLAT B.

IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA), Bulgaria, 19 - 21 June 2013 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/inista.2013.6577626
  • Country: Bulgaria
  • Yıldız Technical University Affiliated: Yes

Abstract

This paper focuses on improving the performance of Adaboost (Adaptive Boosting) by using weak classifiers that make classification with a confidence score. Single thresholds and nearest neighbor classifiers are used as base classifiers. The proposed method is applied to the problem of pedestrian detection in still images. Haar-like basic features are used to construct weak classifiers.