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This paper presents a simple and active calibration technique of camera-projector systems based on planar homography. From the camera image of a planar calibration pattern, we generate a projector image of the pattern through the homography between the camera and the projector. To determine the coordinates of the pattern corners from the view of the projector, we actively project a corner marker from...
Interest points are widely used in computer vision applications such as camera calibration, robot localization and object tracking that require fast and efficient feature matching. A large number of techniques have been proposed in the literature. This paper evaluates the state of art techniques for interest point detection including execution time and suitability for real time applications. Such...
Camera calibration is one of critical steps in computer vision, also an exhaustive process because substantial human computer interactions are frequently required to deal with the matching problem. In this paper, an automatic matching method of markers for camera calibration is presented based on the local architecture characteristics of a new planar circle pattern, which can be applied to a wide...
A fast and accurate coded marker identification method is presented in this paper. The method combines image processing techniques with prior information of markerpsilas appearance and shape. The deformation of the circle caused by projection is considered so that the marker can be recognized correctly. The experiments demonstrate the robustness and accuracy of our method.
We propose a new method for sampling camera response functions: temporally mixing two uncalibrated irradiances within a single camera exposure. Calibration methods rely on some known relationship between irradiance at the camera image plane and measured pixel intensities. Prior approaches use a color checker chart with known reflectances, registered images with different exposure ratios, or even the...
A simple method for lens calibration is presented. The method uses a fiducial disc and straightedge which are placed imprecisely within the field of view. Several inexpensive 6mm lenses and CCD cameras were used to validate the method. It is fast and accurate to a variance of less than half a pixel, which makes it a useful tool for computer vision.
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