Paper Info
Title
Online Single Person Tracking For Unmanned Aerial Vehicles: Benchmark And New Baseline
Abstract
Online tracking a specific person from a low-altitude unmanned aerial vehicle (UAV) is a very interesting and challenging problem to be solved. However, there exists no large-scale aerial video dataset regarding this online single person tracking (OSPT) task. To promote the study of the OSPT problem in UAV, we first construct a new benchmark dataset including 100 fully annotated aerial videos with nearly 130K frames and 11 challenging factors. Second, we evaluate several state-of-the-art online trackers with real-time performance using our dataset, considering the potential applications in the UAV platform. In addition, with respect to the OSPT problem, we attempt to design a new baseline method with the combination of tracking, detection and re-identification and conduct detailed analysis of different components. This method achieves much better performance than the existing online trackers, which will serve as a new baseline for our benchmark.
Year
DOI
Venue
2019
10.1109/icassp.2019.8682449
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Object Tracking, UAV, Benchmark
Computer vision,BitTorrent tracker,Aerial video,Pattern recognition,Task analysis,Computer science,Artificial intelligence,Benchmark (computing)
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
zhihui wang13912.86
Zihao Liu210.68
Dong Wang332614.06
Shuang Wang44610.94
Yunwei Qi5131.18
Huchuan Lu64827186.26