@inproceedings{50f9959813884716aef394b8b419d655,
title = "Pedestrian detection from still images",
abstract = "In this work, a pedestrian detection method based on adaptive boosting is proposed. The proposed method works on still images. The features utilized in the work are derived from Haar-like templates. An Adaboost classifier is utilized for both feature selection and classification. To show the effectiveness of the proposed algorithm, the system is trained by using Nicta Pedestrian Dataset and tested by using Penn Fudan Pedestrian Dataset. The experimental result shows the proposed method's effectiveness.",
keywords = "Adaboost, Haar-like features, pedestrian detection, rectangular features",
author = "Tetik, \{Yusuf Engin\} and B{\"u}lent Bolat",
year = "2011",
doi = "10.1109/INISTA.2011.5946164",
language = "English",
isbn = "9781612849195",
series = "INISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications",
pages = "540--544",
booktitle = "INISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications",
note = "2011 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2011 ; Conference date: 15-06-2011 Through 18-06-2011",
}