Pedestrian Detection with an Improved Adaboost
IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA), Bulgaristan, 19 - 21 Haziran 2013, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/inista.2013.6577626
- Basıldığı Ülke: Bulgaristan
- Yıldız Teknik Üniversitesi Adresli: Evet
Özet
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.