Probability Density Estimation for Object Recognition in Unmanned Aerial Vehicle Application

被引：0
|
作者：
Kharchenko, V. P. [1 ]
Kukush, A. G. [2 ]
Kuzmenko, N. S. [3 ]
Ostroumov, I. V. [3 ]
机构：
[1] Natl Aviat Univ, Kiev, Ukraine
[2] Taras Shevchenko Natl Univ Kyiv, Fac Mech & Math, Kiev, Ukraine
[3] Purdue Univ, Sch Aeronaut & Astronaut, W Lafayette, IN 47907 USA
来源：
2017 IEEE 4TH INTERNATIONAL CONFERENCE ACTUAL PROBLEMS OF UNMANNED AERIAL VEHICLES DEVELOPMENTS (APUAVD) | 2017年
关键词：
Bayesian approach; frame; Nadaraya-Watson estimate; nonparametric regression; object recognition; probability density function; unmanned aerial vehicle; video-stream;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The problem of object recognition in Unmanned Aerial Vehicle application is considered. Probabilistic Bayesian approach in object recognition is used. The accuracy of object recognition depends directly on the quality of prior data and accuracy of object parameters description. An approach for probability density estimation based of regression model is represented. Probability density functions are estimated by learning samples. The proposed approach is verified by laboratory experiment with video recording of object in rotatable platform.
引用
收藏
页码：233 / 236
页数：4
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