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

被引：0
作者：
Francesco Battistone
Alfredo Petrosino
Vincenzo Santopietro
机构：
[1] University of Naples Parthenope,Department of Science and Technology
来源：
Journal of Signal Processing Systems | 2018年 / 90卷
关键词：
Tracking; Online learning; Outlier detection; Drone; Jetson; GPU;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：891 / 900
页数：9
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