DocumentCode :
510243
Title :
The Depth Estimate of Interesting Points from Monocular Vision
Author :
Lin, Xiangming ; Wei, Hui
Author_Institution :
Sch. of Comput. Sci., Fudan Univ., Shanghai, China
Volume :
3
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
190
Lastpage :
195
Abstract :
We present a novel method to estimate the depth and the spatial locations of points in the three-dimensional scene from monocular vision. First, we take photos when the camera is moving forward and obtain a sequence of photos of a scene. From this sequence of photos, we choose two photos. From these two photos, we can estimate the spatial position of points in the scene. Second, let a corner detector detect the corners on the latter image of the two ordered photos. Third, by using a novel method we can search the points on the former photo which match the corners on the latter image. Fourth, calculate the depths and the spatial locations of the points in the scene whose projections are the corners, by using a formula this paper will present. Compared with previous techniques estimating the depths or positions, our approach does not need any geometric clues, and the required conditions are that take photos while moving to the exactly forward direction. In addition, experiments are carried out to validate each proposed method and algorithm, and the experimental results demonstrate the efficiency of every proposed method and algorithm.
Keywords :
computer vision; estimation theory; motion estimation; corner detector; depth estimate; monocular vision; motion estimation; spatial locations; Cameras; Computer science; Detectors; Eyes; Head; Hydrogen; Layout; Robot vision systems; Robotics and automation; Stereo vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.131
Filename :
5376602
Link To Document :
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