Real-time transmission tower detection from video based on a feature descriptor

被引:19
|
作者
Ceron, Alexander [1 ,2 ]
Mondragon, Ivan [3 ]
Prieto, Flavio [4 ]
机构
[1] Univ Nacl Colombia, Dept Syst Engn & Comp, Carrera 30 45-03, Bogota, Colombia
[2] Univ Militar Nueva Granada, Multimedia Engn Program, Fac Engn, Cra 11 101-80, Bogota, Colombia
[3] Pontificia Univ Javeriana, Dept Ind Engn, Carrera 7 40-69, Bogota, Colombia
[4] Univ Nacl Colombia, Dept Mech & Mechatron Engn, Bogota, Colombia
关键词
D O I
10.1049/iet-cvi.2015.0477
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study, the authors propose a new method for transmission tower detection that involves the use of visual features and the linear content of the scene. For this process, they developed a descriptor based on a grid of two-dimensional feature descriptors that is useful not only for object detection, but also for tracking the area of interest. For the detection and classification, they used a support vector machine. The experiments were conducted with a dataset of real world images from transmission tower videos that were used to validate the strategy by comparing it with the ground truth. The results showed that the obtained method is fast and appropriate for tower detection in video sequences of environments that include rural and urban areas. The detection took less than 50 ms and was faster than other methods.
引用
收藏
页码:33 / 42
页数:10
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