DocumentCode
635069
Title
Depth and normal vector identification of an unknown slope from a UAV using a single camera
Author
Zhichao Liu ; Jianliang Wang ; Poh Eng Kee ; Sundaram, Suresh
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear
2013
fDate
23-26 June 2013
Firstpage
1
Lastpage
6
Abstract
This paper presents a novel vision-based system to estimate the normal vector of an unknown slope and the range from a camera fixed on a UAV to the slope using a single camera. An exact point-based image moments model considering the camera´s focal length is presented. Using the model, a fast estimator is designed to estimate the image flow with high precision. The continuous model is then discretized using Taylor series method. Finally, a particle filter is used to obtain a solution to the estimation problem. The whole system estimates simultaneously the normal vector of the unknown slope and the depth from the camera on the UAV to the slope.
Keywords
autonomous aerial vehicles; image sensors; object detection; robot vision; Taylor series method; UAV; camera focal length; depth vector identification; image flow; normal vector identification; point-based image moments model; unknown slope; vision-based system; Adaptation models; Cameras; Equations; Mathematical model; Observers; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ASCC), 2013 9th Asian
Conference_Location
Istanbul
Print_ISBN
978-1-4673-5767-8
Type
conf
DOI
10.1109/ASCC.2013.6606215
Filename
6606215
Link To Document