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Ordered Minimum Distance Bag-of-Words Approach for Aerial Object Identification

Unlu, Eren and Zenou, Emmanuel and Rivière, Nicolas Ordered Minimum Distance Bag-of-Words Approach for Aerial Object Identification. (2017) In: 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 29 August 2017 - 1 September 2017 (Lecce, Italy).

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Abstract

Detecting potential aerial threats like drones with computer vision is at the paramount of interest for the protection of critical locations.This type of a system should prevent efficiently the false alarms caused by non-malign objects such as birds, which intrude the image plane. In this paper, we propose an improved version of a previously presented Speeded-up Robust Feature Transform (SURF) based algorithm, referred as Ordered Minimum Distance Bag-of-Words (omidBoW) to discriminate drones, birds and background from the patches, using an extended histogram set. We show that a SURF based object recognition can be well integrated to this context and this improved algorithm can increase accuracy up to 16% compared to regular bag-ofwords approach.

Item Type:Conference or Workshop Item (Paper)
Additional Information:ISBN 978-1-5386-2939-0/17
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
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Deposited By: Eren Unlu
Deposited On:25 Sep 2017 12:03

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