Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9613
Title: Affordable person detection in omnidirectional cameras using radial integral channel features
Authors: Demiröz, Barış Evrim
Salah, Albert Ali
Baştanlar, Yalın
Akarun, Lale
Baştanlar, Yalın
Baştanlar, Yalın
Izmir Institute of Technology. Computer Engineering
Keywords: Omnidirectional camera
Object detection
Human detection
Person detection
Integral channel features
Integral image
Issue Date: 2019
Publisher: Springer Verlag
Abstract: Omnidirectional cameras cover more ground than perspective cameras, at the expense of resolution. Their comprehensive field of view makes omnidirectional cameras appealing for security and ambient intelligence applications. Person detection is usually a core part of such applications. Conventional methods fail for omnidirectional images due to different image geometry and formation. In this study, we propose a method for person detection in omnidirectional images, which is based on the integral channel features approach. Features are extracted from various channels, such as LUV and gradient magnitude, and classified using boosted decision trees. Features are pixel sums inside annular sectors (doughnut slice shapes) contained by the detection window. We also propose a novel data structure called radial integral image that allows to calculate sums inside annular sectors efficiently. We have shown with experiments that our method outperforms the previous state of the art and uses significantly less computational resources.
URI: https://doi.org/10.1007/s00138-019-01016-w
https://hdl.handle.net/11147/9613
ISSN: 0932-8092
1432-1769
0932-8092
1432-1769
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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