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Computed from a calibration pattern and known camera intrinsic parameters.
Hoang et al. [16] also use a calibration pattern with a triangular hole.
Computed from a calibration pattern as seen from a second high-resolution camera with known intrinsic parameters and known spatial relation to the evaluated camera.
The camera parameters (intrinsic and extrinsic) were computed by observing a calibration pattern at different locations and orientations in the scene [9].
Nair et al. state three methods to acquire such ground truth [9]: Computed from a calibration pattern and known camera intrinsic parameters Computed from a calibration pattern as seen from a second high-resolution camera with known intrinsic parameters and known spatial relation to the evaluated camera.
The camera parameters are determined once, at the beginning of the season, by observing a calibration pattern at different positions and orientations in the scene, as described in [9].
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Here, a new calibration pattern, visible to both sensors is proposed.
A new calibration pattern was designed and the image of the calibration pattern was captured by using a wide-angle lens.
Our approach does not rely on the knowledge of the sensor model, on the use of a specific calibration pattern or on external SLAM systems to track the device position.
Towards this goal, we first design a special calibration pattern utilizing the concept of cross-ratio, which makes it easy to extract and identify feature points, so that we can calculate the camera parameters from the visible portion of the pattern in real-time.
Ha et al. [15] propose a new, specifically constructed calibration pattern with a triangular hole to reduce the number of calibration images.
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