• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.9
• /
• pp.856-860
• /
• 2006

A CCD camera is used to determine the position of the point sources that influence the measurement accuracy in the absolute interferometer. The principle of determination method is based on the GPS in which the position is determined by more than 3 distance information from the known positions. Two-dimensional array of photo-detectors in the CCD camera is used as known positions. Performing optimization of the cost function constructed with phase values measured at each pixel on the CCD camera, the position coordinates of each source is precisely determined.

• Journal of Korea Multimedia Society
• /
• v.10 no.12
• /
• pp.1566-1576
• /
• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• Journal of Korea Multimedia Society
• /
• v.10 no.12
• /
• pp.1591-1600
• /
• 2007

Camera position information from 2D face image is very important for that make the virtual 3D face model synchronize to the real face at view point, and it is also very important for any other uses such as: human computer interface (face mouth), automatic camera control etc. We present an algorithm to detect human face region and mouth, based on special color features of face and mouth in $YC_bC_r$ color space. The algorithm constructs a mouth feature image based on $C_b\;and\;C_r$ values, and use pattern method to detect the mouth position. And then we use the geometrical relationship between mouth position information and face side boundary information to determine the camera position. Experimental results demonstrate the validity of the proposed algorithm and the Correct Determination Rate is accredited for applying it into practice.

• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.239-242
• /
• 2003

In this paper, we propose how to determine the optimal camera position using inverse kinematics of virtual link model and manipulability measure. We model the variable distance and viewing direction between a target object and a camera position as a virtual link. And, by using inverse kinematics of virtual link model, we find out regions that satisfy the direction and distance constraints for the observation of target object. The solution of inverse kinematics of virtual link model simultaneously satisfies camera accessibility as well as a direction and distance constraints. And we use a manipulability measure of active camera system in order to determine an optimal camera position among the multiple solutions of inverse kinematics. By using the inverse kinematics of virtual link model and manipulability measure, the optimal camera position in order to observe a target object can be determined easily and rapidly.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.219-222
• /
• 1996

During the navigation of mobile robot, one of the essential task is to determination the absolute location of mobile robot. In this paper, we proposed a method to determine the position of the camera from a landmark through the visual image of a quadrangle typed landmark using neural network. In determining the position of the camera on the world coordinate, there is difference between real value and calculated value because of uncertainty in pixels, incorrect camera calibration and lens distortion etc. This paper describes the solution of the above problem using BPN(Back Propagation Network). The experimental results show the superiority of the proposed method in comparison to conventional method in the performance of determining camera position.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.8 no.6
• /
• pp.26-34
• /
• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.276-276
• /
• 2000

This paper presents the efficient algorithms for the pose determination of a circular object with and without a priori knowledge of the object radius. The developed algorithms valid for a circular object are the result of the elaboration of Ma's work [2], which determines the pose of a conic object from two perspective views. First, the geometric constraint of a circular object and its projection on the image plane of a camera is described. The number of perspective views required for the object pose determination with and without a priori knowledge of the object radius is also discussed. Second, with a priori knowledge of the object radius, the pose of a circular object is determined from a single perspective view. The object pose information, expressed by two surface normal vectors and one position vector, is given in a closed form and with no ambiguity. Third, without a priori knowledge of the object radius, the pose of a circular object is determined from two perspective views. While the surface normal vectors are obtained from the first view, the position vector is obtained from the two views.

• Journal of Advanced Navigation Technology
• /
• v.17 no.3
• /
• pp.354-360
• /
• 2013

A stereo vision analysis was performed for motion and depth control of unmanned vehicles. In stereo vision, the depth information in three-dimensional coordinates can be obtained by triangulation after identifying points between the stereo image. However, there are always triangulation errors due to several reasons. Such errors in the vision triangulation can be alleviated by careful arrangement of the camera position and orientation. In this paper, an approach to the determination of the optimal position and orientation of camera is presented for unmanned vehicles.

• Journal of Mechanical Science and Technology
• /
• v.17 no.10
• /
• pp.1431-1442
• /
• 2003

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. To be an efficient and precise mobile-task robot, the control uncertainties in the mobile robot should be resolved. Unless the mobile robot provides an accurate and stable base, the task robot cannot perform various tasks. For the control of the mobile robot, an absolute position sensor is necessary. However, on account of rolling and slippage of wheels on the ground, there does not exist any reliable position sensor for the mobile robot. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. For this calibration, a camera is attached on the top of the task robot to capture the images of the objects. These images are used to estimate the pose of the camera itself with respect to the known objects. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and propagated to get the pose of a mobile robot. Two types of objects are used here as samples of work-pieces: a polygonal and a cylindrical object. With these two samples, the proposed active calibration scheme is verified experimentally.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.590-593
• /
• 2001

In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.