Camera Calibration Technique Research Articles

三次元画像処理流速計による複雑形状流路内流れの測定

The three-dimensional particle tracking velocimeter (3-D PTV) is a powerful tool for measuring the instantaneous three-dimensional distributions of the velocity vectors. Despite of its significant ability, it can be applied only to the flow field in a simple geometry, because of its complex camera calibration procedure. Although there have been made some modifications that handle the refraction at the glass walls implicitly in the camera parameters, but their applications are still limited to the case of parallel planes. Presently, a new method is proposed that calculates all the refractions at any surface explicitly. Thus, one can avoid the complexity in the camera calibration and can measure any flow field in the complex geometry, if the shape of which is known by the numerics. The principle of the new camera calibration technique and the procedures for the practical measurement in a circular curved pipe is shown in this study.

Recognizing cylindrical objects by single camera views

A new approach to recognition of cylindrical objects by single camera views using camera calibration, surface backprojection, and model matching techniques is proposed. Cylindrical objects to be recognized can be of different radii and heights. Both the silhouette shapes and the surface patterns of objects are utilized in the recognition scheme. A new camera calibration technique is first employed to compute the camera parameters analytically using a single camera view of the object. A surface backprojection technique is then adopted to reconstruct the pattern on the surface patch of the input object. The reconstructed surface pattern is finally matched with that of each object model, using a partial shape matching technique to find the best matching surface patch pattern of the models, from which the input object is classified accordingly. Experimental results showing the feasibility of the proposed approach are also included.

2 三次元画像処理流速計による複雑形状流路内流れの測定

The three-dimensional particle tracking velocimeter (3-D PTV) is a powerful tool for measuring the instantaneous three-dimensional distributions of the velocity vectors. Despite of its significant ability, it can be applied only to the flow field in a simple geometory, because of its complex camera calibration procedure. Although there have been made some modifications that handle the refraction at the glass walls implicitly in the camera parameters, but their applications are still limited to the case of parallel planes. Presently, a new method is proposed that calculates all the refractions at any surface explicitly. Thus, one can avoid the complexity in the camera calibration and can measure any flow field in the complex geometry, if the shape of which is known by the numerics. The principle of the new camera calibration technique and the procedures for the practical mesurement in a circular curved pipe is shown in this study.

Accurate linear technique for camera calibration considering lens distortion by solving an eigenvalue problem

A new technique for calibrating a camera with high accuracy and low computational cost is proposed. The geometric camera parameters considered include camera position, orientation, focal length, radial lens distortion, pixel size, and optical axis piercing point. With this method, the camera parameters to be estimated are divided into two parts: the radial lens distortion coefficient κ and a composite parameter vector c composed of all the above-mentioned geometric camera parameters other than κ. Instead of using nonlinear optimization techniques, the estimation of κ is transformed into an eigenvalue problem of an 8 x 8 matrix. The method is fast because it requires only linear computation; it is accurate because the effect of the lens distortion is considered and because all the information contained in the calibration points is used. Computer simulations and real experiments show that the calibration method can achieve an accuracy of 1 part in 10,000 in 3-D measurement, which is better than that of the well-known method proposed by R. Y. Tsai.

On single-scanline camera calibration

A method for calibrating single scanline CCD cameras is described. It is shown that the more classical 2D camera calibration techniques are necessary but not sufficient for solving the 1D camera calibration problem. A model for single scanline cameras is proposed, and a two-step procedure for estimating its parameters is provided. It is also shown how the extrinsic camera parameters can be determined geometrically without making explicit the intrinsic camera parameters. The accuracy of the calibration method is analyzed through an application example.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

3-D camera calibration using vanishing point concept

A three-dimensional (3-D) camera calibration technique that uses two-dimensional (2-D) grid paper and a vanishing point concept was developed and tested. The calibration technique does not require knowledge of the precise location of the calibration target as other calibration techniques require. The algorithm developed consists of the following steps: (1) Use a point-finder program with a subpixel interpolation technique to identify the points on a grid. (2) Apply an equalization procedure. (3) Use a line-finder program with a statistical linear regression technique to identify a line. (4) Repeat Steps 1 and 2 until all the lines are found. Then divide the lines into two groups—horizontal and vertical. (5) Determine one vanishing point for all the horizontal lines and one vanishing point for all the vertical lines. (6) Using the same vanishing point concept, determine the vanishing points for the planes of sight in space (horizontal and vertical). (7) Determine the camera location and rotational matrix. By using statistical methods, resolution at the subpixel level was achieved. Commercially available components were used in the vision system for this project. The results of the two tests showed that a low-cost vision system can make 3-D coordinate measurements as exact as 5 mils (0.005 inches) in accuracy and 1 mil in repeatability when properly set up and used with this calibration technique.

A camera calibration technique using three sets of parallel lines

A method is presented for three-dimensional camera calibration in which the rotation parameters are decoupled from the translation parameters. The rotation parameters are obtained by projecting three sets of parallel lines independently of the translation parameters and the imaging distance from the lens to the image plane. The virtual line passing through the image center, which is calculated by perspective projection of a set of parallel lines, depends only on the rotation parameters. The translation parameters and the imaging distance are analytically obtained. Experimental results show that the camera model can be reconstructed accurately. >

A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses

A new technique for three-dimensional (3D) camera calibration for machine vision metrology using off-the-shelf TV cameras and lenses is described. The two-stage technique is aimed at efficient computation of camera external position and orientation relative to object reference coordinate system as well as the effective focal length, radial lens distortion, and image scanning parameters. The two-stage technique has advantage in terms of accuracy, speed, and versatility over existing state of the art. A critical review of the state of the art is given in the beginning. A theoretical framework is established, supported by comprehensive proof in five appendixes, and may pave the way for future research on 3D robotics vision. Test results using real data are described. Both accuracy and speed are reported. The experimental results are analyzed and compared with theoretical prediction. Recent effort indicates that with slight modification, the two-stage calibration can be done in real time.

On the Parametrization of the Three-Dimensional Rotation Group

Parameterization of group of rotations of Euclidean three-dimensional space applied to integration of rigid body motion equations