• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.208-214
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• 2014

In this paper, in order to solve the problems of a narrow viewing angle and the flip effect in a three-dimensional (3D) integral imaging display, we propose an improved system by using an eye tracking method based on the Kinect sensor. In the proposed method, we introduce two types of calibration processes. First process is to perform the calibration between two cameras within Kinect sensor to collect specific 3D information. Second process is to use a space calibration for the coordinate conversion between the Kinect sensor and the coordinate system of the display panel. Our calibration processes can provide the improved performance of estimation for 3D position of the observer's eyes and generate elemental images in real-time speed based on the estimated position. To show the usefulness of the proposed method, we implement an integral imaging display system using the eye tracking process based on our calibration processes and carry out the preliminary experiments by measuring the viewing angle and flipping effect for the reconstructed 3D images. The experimental results reveal that the proposed method extended the viewing angles and removed the flipping images compared with the conventional system.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.883-886
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• 1998

In order to detect the user's gaze position on a monitor by computer vision, the accurate estimations of 3D positions and 3D motion of facial features are required. In this paper, we apply a EKF(Extended Kalman Filter) to estimate 3D motion estimates and assumes that its motion is "smooth" in the sense of being represented as constant velocity translational and rotational model. Rotational motion is defined about the orgin of an face-centered coordinate system, while translational motion is defined about that of a camera centered coordinate system. For the experiments, we use the 3D facial motion data generated by computer simulation. Experiment results show that the simulation data andthe estimation results of EKF are similar.e similar.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.48-60
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• 2007

In previous researches for iris feature extraction, they transform a original iris image into rectangular one by stretching and interpolation, which causes the distortion of iris patterns. Consequently, it reduce iris recognition accuracy. So we are propose the method that extracts iris feature by using polar coordinates without distortion of iris patterns. Our proposed method has three strengths compared with previous researches. First, we extract iris feature directly from polar coordinate circular iris image. Though it requires a little more processing time, there is no degradation of accuracy for iris recognition and we compares the recognition performance of polar coordinate to rectangular type using by Hamming Distance, Cosine Distance and Euclidean Distance. Second, in general, the center position of pupil is different from that of iris due to camera angle, head position and gaze direction of user. So, we propose the method of iris feature detection based on polar coordinate circular iris region, which uses pupil and iris position and radius at the same time. Third, we overcome override point from iris patterns by using polar coordinates circular method. each overlapped point would be extracted from the same position of iris region. To overcome such problem, we modify Gabor filter's size and frequency on first track in order to consider low frequency iris patterns caused by overlapped points. Experimental results showed that EER is 0.29%, d' is 5,9 and EER is 0.16%, d' is 6,4 in case of using conventional rectangular image and proposed method, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.839-846
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• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.60-70
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• 2000

In this paper a 3D position measuring device that finds the 3D position of an arbitarily placed object using a camersa system is introduced. The camera system consists of three stepping motors and a CCD camera and a laser. The viewing direction of the camera is controlled by two stepping motors (pan and tilt motors) and the direction of a laser is also controlled by a stepping motors(laser motor). If an object in a remote place is selected from a live video image the x,y,z coordinates of the object with respect to the reference coordinate system can be obtained by calculating the distance from the camera to the object using a structured light scheme and by obtaining the orientation of the camera that is controlled by two stepping motors. The angles o f stepping motors are controlled by a SGI O2 workstation through a parallel port. The mathematical model of the camera and the distance measuring system are calibrated to calculate an accurate position of the object. This 3D position measuring device can be used to acquire information that is necessary to monitor a remote place.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.91-96
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• 2019

In this study, a system to increase the expressiveness of existing standard terminology using three-dimensional (3D) data is designed. We analyze the existing medical terminology system by searching the reference literature and perform an expert group focus survey. A human body image is generated using a 3D modeling tool. Then, the anatomical position of the human body is mapped to the 3D coordinates' identification (ID) and metadata. We define the term to represent the 3D human body position in a total of 12 categories, including semantic terminology entity and semantic disorder. The Blender and 3ds Max programs are used to create the 3D model from medical imaging data. The generated 3D human body model is expressed by the ID of the coordinate type (x, y, and z axes) based on the anatomical position and mapped to the semantic entity including the meaning. We propose a system of standard terminology enabling integration and utilization of the 3D human body model, coordinates (ID), and metadata. In the future, through cooperation with the Electronic Health Record system, we will contribute to clinical research to generate higher-quality big data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.12
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• pp.1002-1016
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• 1990

This paper described design and implementation of stereo vision system, and also, proposed method for displacement estimation of 3-D moving object using this system. The extraction of moving object is obtained by difference image algorithm. Geometrical position of 3-D moving object is calculated form the mapping of center area of two's 2-D object. 3-D coordinate position produced space depth, moving velociity, distance, moving track and proved displacement estimation of 3-D moving object.

• 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.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.136-145
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• 1997

As a 3D mesh model consists of a lot of vertices and polygons and each vertex position is represented by three 32 bit floating-point numbers in a 3D coordinate, the amount of data needed for representing the model is very excessive. Thus, in order to store and/or transmit the 3D model efficiently, a 3D model compression is necessarily required. In this paper, a 3D model compression method using PRVQ (predictive residual vector quantization) is proposed. Its underlying idea is based on the characteristics such as high correlation between the neighboring vertex positions and the vectorial property inherent to a vertex position. Experimental results show that the proposed method obtains higher compression ratio than that of the existing methods and has the advantage of being capable of transmitting the vertex position data progressively.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1122-1129
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• 2009

Recently taping robot with smart recognition function have been studied in the coil manufacturing field. Due to the difficulty of 3D surface processing from the complicated working environment, it is not easy to accomplish smart tape attachment motion with non-contact sensor. To solve these problems the applicable surface recognition algorithm and a flexible sensing device has been recommended. In this research, the fusion method between 1D displacement and 3D laser scanner is applied for robust tape attachment about cold rolled coil. With these sensors we develop a two-step exploration and the smart algorithm for the awareness of non-aligned coil's information. In the proposed robot system for tape attachment, the problem is reduced to coil's radius searching with laser displacement sensor at first, and then position and orientation detection with 3D laser scanner. To get the movement at the robot's base frame, the hand-eye compensation between robot's end effector and sensing device should be also carried out respectively. In this paper, we examine the auto-coordinate transformation method in the calibration step for the real environment usage. From the experimental results, it was shown that the taping motion of robot had a robust under the non-aligned cold rolled coil.