Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles

Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles The paper presents the development of a real time tracking system, named Watch Out, that is able to efficiently run on an Nvidia Jetson board mounted on a UAV (Unmanned Aerial Vehicle). The approach to long term video tracking implemented in Watch Out is named Best Structured Tracker (BST): a set of local trackers independently tracks patches of the original target in an online learning manner, while an outlier detection procedure filters out the less meaningful ones, and a resampling procedure allows to correctly reinitialise the trackers that have been filtered out. Performance of the tracking algorithm has been verified both on VOT2016 challenge datasets and in real situations using an Nvidia Jetson board mounted on a drone. Results show that the proposed system can track almost every possible target in real time. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Signal Processing Systems Springer Journals

Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Signal,Image and Speech Processing; Circuits and Systems; Electrical Engineering; Image Processing and Computer Vision; Pattern Recognition; Computer Imaging, Vision, Pattern Recognition and Graphics
ISSN
1939-8018
eISSN
1939-8115
D.O.I.
10.1007/s11265-017-1279-x
Publisher site
See Article on Publisher Site

Abstract

The paper presents the development of a real time tracking system, named Watch Out, that is able to efficiently run on an Nvidia Jetson board mounted on a UAV (Unmanned Aerial Vehicle). The approach to long term video tracking implemented in Watch Out is named Best Structured Tracker (BST): a set of local trackers independently tracks patches of the original target in an online learning manner, while an outlier detection procedure filters out the less meaningful ones, and a resampling procedure allows to correctly reinitialise the trackers that have been filtered out. Performance of the tracking algorithm has been verified both on VOT2016 challenge datasets and in real situations using an Nvidia Jetson board mounted on a drone. Results show that the proposed system can track almost every possible target in real time.

Journal

Journal of Signal Processing SystemsSpringer Journals

Published: Sep 9, 2017

References

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