NDLI: Aircraft tracking based on fully conventional network and Kalman filter

Content Provider	IET Digital Library
Author	Yang, Jiachen Zhao, Weirong Han, Yurong Ji, Chunqi Jiang, Bin Zheng, Zhihui Song, Houbing
Abstract	Aircraft tracking is a significant technology for military reconnaissance, but there is no efficient algorithm to solve this particular problem. Recently, research based on deep learning for object tracking has developed rapidly, and the performance is greatly improved compared to the traditional methods, so the authors refer to relevant work and make an improvement on the previous research to improve the performance on aircraft tracking. They first learn the idea from region-based fully convolutional networks to perform detection on each frame of video. To avoid the target drift due to the failure of object detection on a certain frame, then they employ Kalman filter (KF) and extended KF together to predict the moving trajectory of the target. Beyond that, this method can confine the valid range based on the size of a target object, which increases the speed of detection. This approach can also correct the bounding box on adjacent frames. The steps are not complicated but have an excellent performance. Through the experiment, it is clear that the proposed method is reasonable and more precise.
Starting Page	1259
Ending Page	1265
Page Count	7
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 8, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5022
Journal	IET Image Processing
Publisher Date	2019-01-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Aircraft Aircraft Tracking Computer Vision And Image Processing Technique Convolutional Neural Nets Deep Learning Detection And Tracking System Extended KF Filtering Method in Signal Processing Image Filtering Kalman Filter Knowledge Engineering Technique Learning in AI Military Computing Military Engineering Computing Military Radar Military Reconnaissance Neural Computing Technique Nonlinear Filter Object Detection Object Tracking Optical, Image And Video Signal Processing Region-based Fully Convolutional Network Target Object Target Tracking Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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