Proceedings of the 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)

A Simulation Method of Generating Multi-view Image of Aircraft Targets

Authors
Yunfeng Liu, Bin Li, Xiaopei Tang, Xiaogang Yang, Yong Tang
Corresponding Author
Yunfeng Liu
Available Online June 2017.
DOI
https://doi.org/10.2991/icmia-17.2017.125How to use a DOI?
Keywords
Data augmentation, Aircraft Targets, Multi-view Transformation, Deep learning
Abstract
Aircraft target detection in airport remote sensing image by deep learning is a hot topic of current research, however, training deep network model needs a large amount of datasets, and there is no website or the specialized agencies to collect remote sensing images of airport. To solve the problem, a multi-view images generation method for aircraft targets is proposed in this paper. Firstly, the aircraft viewpoint transformation detection imaging model was established, and the coordinate transformation is deduced in detail; secondly, a multi-view image simulation algorithm structure was designed, and the realization of the algorithm is introduced in detail. Experimental results show that the method has good simulation effect on remote sensing images of airport and have high use value.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-387-6
ISSN
1951-6851
DOI
https://doi.org/10.2991/icmia-17.2017.125How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yunfeng Liu
AU  - Bin Li
AU  - Xiaopei Tang
AU  - Xiaogang Yang
AU  - Yong Tang
PY  - 2017/06
DA  - 2017/06
TI  - A Simulation Method of Generating Multi-view Image of Aircraft Targets
BT  - 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-17.2017.125
DO  - https://doi.org/10.2991/icmia-17.2017.125
ID  - Liu2017/06
ER  -