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

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.65-72
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• 2010

For developing navigation system of total hip arthroplasty (THA) and evaluating hip joint kinematics, 3-D pose position of the femur and acetabulum in the pelvic coordinate system has been quantified. The pelvic coordinate system is determined by manually indicating pelvic landmarks in multidetector-row computed tomography (MDCT) images. It includes intra- and inter-observer variability, and may result in a variability of THA operation or diagnosis. To reduce the variability of pelvic coordinate system determination, this paper proposes an automated method in MDCT images. The proposed method determines pelvic coordinate system automatically by detecting pelvic landmarks on anterior pelvic plane (APP) from MDCT images. The method calibrates pelvic pose by using silhouette images to suppress the affect of pelvic pose change. As a result of comparing with manual determination, the proposed method determined the coordinate system with a mean displacement of $2.6\;{\pm}\;1.6$ mm and a mean angle error of $0.78\;{\pm}\;0.34$ deg on 5 THA subjects. For changes of pelvic pose position within 10 deg, standard deviation of displacement was 3.7 mm, and of pose was 1.28 deg. We confirmed the proposed method was robust for pelvic pose changes.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.734-739
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• 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. For the control of the mobile robot, an absolute position sensor is necessary. 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. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and that is propagated to getting the pose of a mobile robot. With the experiments in the corridor, the proposed active calibration scheme is verified experimentally.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.1-11
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• 2013

The determination of the pose of the imaging camera is a fundamental problem in computer vision. In the monocular case, difficulties in determining the scene scale and the limitation to bearing-only measurements increase the difficulty in estimating camera pose accurately. Many mobile phones now contain inertial measurement devices, which may lend some aid to the task of determining camera pose. In this study, by means of simulation and real-world experimentation, we explore an approach to monocular camera localization that incorporates both observations of the environment and measurements from accelerometers and gyroscopes. The unscented Kalman filter was implemented for this task. Our main contribution is a novel approach to landmark initialization in a Kalman filter; we characterize the tolerance to noise that this approach allows.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.199-200
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• 2008

머리의 자세 및 움직임 추적은 응시추적 및 시각운율 연구에서 필수적이다. 일반적으로 머리자세를 추정하는 방법은 보정된 카메라를 통해 추출된 얼굴의 특징점 정보를 이용한다. 그러나 실제 응용 분야에서는 보정되지 않은 카메라를 통한 머리 움직임을 추정해야 할 경우가 발생한다. 이에 따라 본 논문에서는 보정되지 않은 하나의 카메라를 이용, 단일특징점 정보를 이용한 머리 자세 추정 방법을 확장하여 최적화 기법을 도입한 다특징점 정보 기반 머리 자세 추정방법에 대하여 논하였다.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 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 Mechanical Science and Technology
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• v.17 no.10
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• pp.1431-1442
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• 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.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.83-91
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• 2004

The determination of camera position and orientation from known correspondences of 3D reference points and their images is known as pose estimation in computer vision or space resection in photogrammetry. This paper discusses estimation of transform parameters using the pattern matching method with 2D images only. In general, the 3D reference points or lines are needed to find out the 3D transform parameters, but this method is applied without the 3D reference points or lines. It uses only two images to find out the transform parameters between two image. The algorithm is simulated using Visual C＋＋ on Windows 98.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.448-451
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• 1999

In this paper, we propose a new object representation method and matching algorithm for object recognition using a 3-fingered robot hand. Each finger tip can measure normal vector and shapes of a contacting surface. Object is represented by the inter-surface description table where the features of a surface are described in the diagonal and the relations between two surfaces are in the upper diagonal. Based on this table, a fast and the efficient matching algorithm has been proposed. This algorithm can be applied to natural quadric objects.

• Journal of Food Hygiene and Safety
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• v.12 no.1
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• pp.71-77
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• 1997

Sulfonamides, a therapeutically important group of antimicrobial drugs, are widely used to treat and prevent the acute systemic and skin infections in dairy cattle. They also pose an economic hazard through inhibition of growth of dairy starter cultures. This study was carried out to compare four screening methods for detection of sulfamethazine in milk and determine the positive milk sample by HPLC method. Sulfamethazine was used to spike at five levels of sulfamethazine. The Lac-Tek test and CharmII test were also consistent better than TTCII test and Delvo SP test in sulfamethazine detection. Analysis probabilities of obtaining a positive response with TTCII test and Delvo SP test assay at 50 ppb sulfamethazine level in milk samples were only 14%, 42% each. Whereas using the Lac-Tek test and CharmII test would have resulted in 100% identification of the five levels. Determination of sufamethazine using the HPLC method in the spiked milk were 10.64, 19.30, 30.76,38.83 and 50.23 ppb, respectively.