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PCM
2015
Springer

Pattern Feature Detection for Camera Calibration Using Circular Sample

3 years 9 months ago
Pattern Feature Detection for Camera Calibration Using Circular Sample
Camera calibration is a process to find camera parameters. Camera parameter consists of intrinsic and extrinsic configuration and it is important to deal with the three-dimensional (3-D) geometry of the cameras and 3-D scene. However, camera calibration is quite annoying process when the number of cameras and images increase because it is operated by hand to indicate exact points. In order to eliminate the inconvenience of a manual manipulation, we propose a new pattern feature detection algorithm. The proposed method employs the Harris corner detector to find the candidate for the pattern feature points in images. Among them, we extract valid pattern feature points by using a circular sample. Test results show that this algorithm can provide reasonable camera parameters compared to camera parameters using the Matlab calibration toolbox by hand but eliminated a burden of manual operation.
Dong-Won Shin, Yo-Sung Ho
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where PCM
Authors Dong-Won Shin, Yo-Sung Ho
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