Pattern Feature Detection for Camera Calibration Using Circular Sample

8 years 5 days ago

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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

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