• Title/Summary/Keyword: 3-D Object Position

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3D Pose Estimation of a Circular Feature With a Coplanar Point (공면 점을 포함한 원형 특징의 3차원 자세 및 위치 추정)

  • Kim, Heon-Hui;Park, Kwang-Hyun;Ha, Yun-Su
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.5
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    • pp.13-24
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    • 2011
  • This paper deals with a 3D-pose (orientation and position) estimation problem of a circular object in 3D-space. Circular features can be found with many objects in real world, and provide crucial cues in vision-based object recognition and location. In general, as a circular feature in 3D space is perspectively projected when imaged by a camera, it is difficult to recover fully three-dimensional orientation and position parameters from the projected curve information. This paper therefore proposes a 3D pose estimation method of a circular feature using a coplanar point. We first interpret a circular feature with a coplanar point in both the projective space and 3D space. A procedure for estimating 3D orientation/position parameters is then described. The proposed method is verified by a numerical example, and evaluated by a series of experiments for analyzing accuracy and sensitivity.

An Adaptive Classifier for 3-D Planar Object Recognition Based on Uncertainty of Features by Binocular Stereo Method (Binocular Stereo 방법에 의한 3차원 평면 물체의 특징값의 불확실성을 고려한 적응분류기)

  • 권중장;김성대
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.4
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    • pp.92-103
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    • 1993
  • In this paper, we propose an adaptive classifier based on uncertainty of features for 3D planar object recognition. First, we investigate the uncertainty of depth information and the feature values of 3D planar object by numerical method. And, we observed that the statistical behavior of feature is dependent on the position and orientation of objects. After that, the approximation of the statistical behavior is executed. Subsequently, the recognition procedure is executed by the adaptive classifier. By computer simulation, we confirmed that the proposed classifier is useful for 3D planar object recognition.

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A Shadow Mapping Technique Separating Static and Dynamic Objects in Games using Multiple Render Targets (다중 렌더 타겟을 사용하여 정적 및 동적 오브젝트를 분리한 게임용 그림자 매핑 기법)

  • Lee, Dongryul;Kim, Youngsik
    • Journal of Korea Game Society
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    • v.15 no.5
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    • pp.99-108
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    • 2015
  • To identify the location of the object and improve the realism in 3D game, shadow mapping is widely used to compute the depth values of vertices in view of the light position. Since the depth value of the shadow map is calculated by the world coordinate, the depth values of the static object don't need to be updated. In this paper, (1) in order to improve the rendering speed, using multiple render targets the depth values of static objects stored only once are separated from those of dynamic objects stored each time. And (2) in order to improve the shadow quality in the quarter view 3D game, the position of the light is located close to dynamic objects traveled along the camera each time. The effectiveness of the proposed method is verified by the experiments according to the different static and dynamics object configuration in 3D game.

An Efficient Method of Scanning and Tracking for AR

  • Park, Yerang;Chin, Seongah
    • International Journal of Advanced Culture Technology
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    • v.7 no.4
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    • pp.302-307
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    • 2019
  • In this paper, we propose an efficient method for AR toolkit Vuforia. In order to increase the scan rate when using the 3D object scanner, the scan rate parameters need to be analyzed in terms of the angle and distance. In addition, in order to increase the tracking rate when tracking an object, the tracking rate has to be evaluated according to the position, complexity, and contrast of the object. To this end, we have defined the difference of scan rate according to angle and distance between camera and object when using object scanner and the recognition time according to object's position, complexity and contrast when tracking object.

3D Position Measurement & Coping using 2 CCD Cameras (2대의 CCD 카메라를 이용한 3차원 위치측정과 코핑)

  • Kang, Won-Chan;Shin, Suck-Doo;Kim, Young-Dong
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.51 no.2
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    • pp.87-93
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    • 2002
  • Accurate acquisition of surface geometries such as machined surfaces, biological surfaces, and deformed parts have been very important technique in scientific study and engineering, especially for system design, manufacturing and inspection. Two-camera method keeps accuracy more than double than mechanical method. In this paper, a new method is studied to acquire 3D geometric data of the small object such as a die in stone model. When the devices, cameras, laser beam and object are in a perfect plane, the calculation is measured by position error 0.025[mm] within. But this paper shows that arbitrarily positioned system can also be used to obtain 3D data. Also, this paper present a method to generate coping surface data with which CAM system can do for milling work.

Real-time Measurement System for 3D Motion of a Body (구조물의 운동에 대한 실시간 측정시스템 개발)

  • Kim, Wonjin;Yoon, Hyesung
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.23 no.5
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    • pp.428-434
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    • 2014
  • Measurement of the absolute displacement of the moving machinery components in three-dimensions (3D) is of critical functional importance. This paper describes the system that measures motion associated with six degrees-of-freedom in 3D. Wire-sensors are used to estimate the positions of an object in a 3D Cartesian coordinate system, based on the values of their initial position and the measured values. For inducing the transfer function, which represents the motion of an object, the number of the minimum measurement points is determined. Also, the experimental measuring device is configured to visualize the behavior of a rectangular object in real-time. The software for measuring the six types of motions is directly programmed using a commercial software.

A Study on Estimating Smartphone Camera Position (스마트폰 카메라의 이동 위치 추정 기술 연구)

  • Oh, Jongtaek;Yoon, Sojung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.6
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    • pp.99-104
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    • 2021
  • The technology of estimating a movement trajectory using a monocular camera such as a smartphone and composing a surrounding 3D image is key not only in indoor positioning but also in the metaverse service. The most important thing in this technique is to estimate the coordinates of the moving camera center. In this paper, a new algorithm for geometrically estimating the moving distance is proposed. The coordinates of the 3D object point are obtained from the first and second photos, and the movement distance vector is obtained using the matching feature points of the first and third photos. Then, while moving the coordinates of the origin of the third camera, a position where the 3D object point and the feature point of the third picture coincide is obtained. Its possibility and accuracy were verified by applying it to actual continuous image data.

Embedding of Objects Using SFM Analysis in Synthetic Image Sequences (합성영상에서의 이동물체의 SFM분석을 통한 물체의 삽입)

  • 최경업;김용철
    • Proceedings of the IEEK Conference
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    • 2000.11c
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    • pp.181-184
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    • 2000
  • This paper presents an experimental system, where an object extracted from an image sequence is embedded into the desired position in a scene. First, a moving object is detected and the 3-D structure is obtained by SFM analysis of comer trajectories. We constrained the motion to translational motion only. Extracted objects are classified by matching with 3-D models and then the structure of the occluded part is restored. Camera calibration is performed for the background scene which will embed the object. Finally, the object is embedded into the scene. In the experiments, we used synthetic image sequences generated with OpenGL library for easy evaluation of the 3-D structure estimation.

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3-D Image Processing Using Laser Slit Beam and Neural Networks (레이저 슬릿빔과 신경망을 이용한 3차원 영상인식)

  • 김병갑;강이석;최경현
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.04a
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    • pp.118-122
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    • 1997
  • This paper presents a 3d image processing which uses neural networks to combine a 2D vision camera and a laser slit beam. A laser slit beam from laser source is slitted by a set of cylindrical lenses and the line image of the slit beam on the object is used to estimate the object parameters. The neural networks allow to get the 3D image parameters such as the size, the position and the orientation form the line image without knowing the camera intrinsic parameters.

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