This paper addresses the linear auto-calibration problem of a pan-tilt-zoom (PTZ) camera. Unlike existing methods, we take full advantage of the offset of the camera center from the rotation center, which is usually non-negligible in bullet-type PTZ cameras. Without any prior assumption, we propose a linear method to recover all intrinsic parameters. First, we successively acquired at least four images using the zoom and rotation capabilities of the PTZ camera. Second, using the homography of two images at the same location but different scales, the principal point and zoom scalar can be linearly recovered. Finally, based on the unknown offset of the camera center and rotation center, we propose a linear method to solve the scale factor in the Kruppa equation and recover the remaining camera intrinsic parameters, namely focal lengths and skew. Synthetic and real experiments demonstrate the feasibility of our approach.
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Linear Auto-calibration of Pan-Tilt-Zoom Cameras With Rotation Center Offset
Semantic Scholar · Engineering · 2023
Abstract
This paper addresses the linear auto-calibration problem of a pan-tilt-zoom (PTZ) camera. Unlike existing methods, we take full advantage of the offset of the camera center from the rotation center, which is usually non-negligible in bullet-type PTZ cameras. Without any prior assumption, we propose a linear method to recover all intrinsic parameters. First, we successively acquired at least four images using the zoom and rotation capabilities of the PTZ camera. Second, using the homography of two images at the same location but different scales, the principal point and zoom scalar can be linearly recovered. Finally, based on the unknown offset of the camera center and rotation center, we propose a linear method to solve the scale factor in the Kruppa equation and recover the remaining camera intrinsic parameters, namely focal lengths and skew. Synthetic and real experiments demonstrate the feasibility of our approach.