Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6957
Title: Joint Exploitation of Features and Optical Flow for Real-Time Moving Object Detection on Drones
Authors: Lezki, Hazal
Öztürk, I. Ahu
Akpınar, M. Akif
Yücel, M. Kerim
Logoğlu, K. Berker
Erdem, Aykut
Erdem, Erkut
Keywords: Moving object detection
Optical flow
UAV
Drones
Embedded vision
Real-time vision
Issue Date: 2019
Publisher: Springer International Publishing Ag
Source: 15th European Conference on Computer Vision (ECCV) -- SEP 08-14, 2018 -- Munich, GERMANY
Series/Report no.: Lecture Notes in Computer Science
Abstract: Moving object detection is an imperative task in computer vision, where it is primarily used for surveillance applications. With the increasing availability of low-altitude aerial vehicles, new challenges for moving object detection have surfaced, both for academia and industry. In this paper, we propose a new approach that can detect moving objects efficiently and handle parallax cases. By introducing sparse flow based parallax handling and downscale processing, we push the boundaries of real-time performance with 16 FPS on limited embedded resources (a five-fold improvement over existing baselines), while managing to perform comparably or even improve the state-of-the-art in two different datasets. We also present a roadmap for extending our approach to exploit multi-modal data in order to mitigate the need for parameter tuning.
URI: https://doi.org/10.1007/978-3-030-11012-3_8
https://hdl.handle.net/20.500.11851/6957
ISBN: 978-3-030-11012-3; 978-3-030-11011-6
ISSN: 0302-9743
1611-3349
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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