DocumentCode
1783695
Title
Research Progress of Obstacle Detection Based on Monocular Vision
Author
Qiang Wu ; Jie Wei ; Xuwen Li
Author_Institution
Coll. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
fYear
2014
fDate
27-29 Aug. 2014
Firstpage
195
Lastpage
198
Abstract
In recent years, unmanned autonomous vehicle navigation technology or UAV research is a hot topic in the field of machine vision, and obstacle detection is the basis of autonomous navigation. In this thesis, the author analyzed the deficiency of stereoscopic vision and classified current monocular obstacle detection algorithms. According to the properties of algorithms, this paper elaborated the function of algorithms based on features, focal length and movements respectively. The author also discussed current situation and prospects for various types of algorithms, including feature extraction and matching, focusing and defocusing model, background subtraction, frame difference and optical flow. Finally, this paper summarized advantages and disadvantages of different autonomous navigation algorithm and discussed the prospect of the monocular obstacle detection technology.
Keywords
collision avoidance; feature extraction; image matching; image sequences; mobile robots; robot vision; stereo image processing; UAV research; background subtraction; defocusing model; feature extraction; feature matching; frame difference; machine vision; monocular obstacle detection algorithms; monocular vision; optical flow; stereoscopic vision; unmanned autonomous vehicle navigation technology; Cameras; Computer vision; Feature extraction; Image motion analysis; Motion compensation; Optical imaging; Optical sensors; feature Matching; monocular vision; obstacle detection; optical flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2014 Tenth International Conference on
Conference_Location
Kitakyushu
Print_ISBN
978-1-4799-5389-9
Type
conf
DOI
10.1109/IIH-MSP.2014.55
Filename
6998301
Link To Document