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Erschienen in: Peer-to-Peer Networking and Applications 2/2015

01.03.2015

Stereo-based region of interest generation for real-time pedestrian detection

verfasst von: Joohee Kim, Maral Mesmakhosroshahi

Erschienen in: Peer-to-Peer Networking and Applications | Ausgabe 2/2015

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Abstract

Pedestrian detection is one of the major goals in advanced driver assistance systems (ADAS) which has become an active research area in recent years. In this paper, we present a stereo based pedestrian detection system by fusing the depth and color data provided by a stereo vision camera on a moving platform. The proposed method uses an adaptive window for region of interest (ROI) generation using dense depth map. The extracted candidates are then applied to a Histogram of Oriented Gradients (HOG) feature descriptor to refine ROIs and Support Vector Machine (SVM) is used to classify them into pedestrian and non-pedestrian classes. The system is tested on a stereo based DAS dataset and results show that our system is able to detect pedestrians with different scales and illumination conditions and in presence of partial occlusion.

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Metadaten
Titel
Stereo-based region of interest generation for real-time pedestrian detection
verfasst von
Joohee Kim
Maral Mesmakhosroshahi
Publikationsdatum
01.03.2015
Verlag
Springer US
Erschienen in
Peer-to-Peer Networking and Applications / Ausgabe 2/2015
Print ISSN: 1936-6442
Elektronische ISSN: 1936-6450
DOI
https://doi.org/10.1007/s12083-013-0234-2

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