• Title/Summary/Keyword: corner point detection

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Mobile Camera-Based Positioning Method by Applying Landmark Corner Extraction (랜드마크 코너 추출을 적용한 모바일 카메라 기반 위치결정 기법)

  • Yoo Jin Lee;Wansang Yoon;Sooahm Rhee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1309-1320
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    • 2023
  • The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

Measurement of Fine 6-DOF Displacement using a 3-facet Mirror (삼면반사체를 이용한 6자유도 미소 변위 측정)

  • 박원식;조형석;변용규;박노열
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.50-50
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    • 2000
  • In this paper, a new measuring system is :proposed which can measure the fine 6-DOF displacement of rigid bodies. Its measurement principle is based on detection of laser beam reflected from a specially fabricated mirror that looks like a triangular pyramid having an equilateral cross-sectional shape. The mirror has three lateral reflective surfaces inclined 45$^{\circ}$ to its bottom surface. We call this mirror 3-facet mirror. The 3-facet mirror is mounted on the object whose 6-DOF displacement is to be measured. The measurement is operated by a laser-based optical system composed of a 3-facet mirror, a laser source, three position-sensitive detectors(PSD). In the sensor system, three PSDs are located at three corner points of a triangular formation, which is an equilateral triangular formation tying parallel to the reference plane. The sensitive areas of three PSDs are oriented toward the center point of the triangular formation. The object whose 6-DOF displacement is to be measured is situated at the center with the 3-facet mirror on its top surface. A laser beam is emitted from the laser source located at the upright position and vertically incident on the top of the 3-fatcet mirror. Since each reflective facet faces toward each PSD, the laser beam is reflected at the 3-facet mirror and splits into three sub-beams, each of which is reflected from the three facets and finally arrives at three PSDs, respectively. Since each PSD is a 2-dimensional sensor, we can acquire the information on the 6-DOF displacement of the 3-facet mirror. From this principle, we can get 6-DOF displacement of any object simply by mounting the 3-facet mirror on the object. In this paper, we model the relationship between the 6-DOF displacement of the object and the outputs of three PSDs. And, a series of simulations are performed to demonstrate the effectiveness of the proposed method. The simulation results show that the proposed sensing system can be an effective means of obtaining 3-dimensional position and orientation of arbitrary objects.

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Robust Semi-auto Calibration Method for Various Cameras and Illumination Changes (다양한 카메라와 조명의 변화에 강건한 반자동 카메라 캘리브레이션 방법)

  • Shin, Dong-Won;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.21 no.1
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    • pp.36-42
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    • 2016
  • Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.