• Title/Summary/Keyword: 상대위치보정

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Geometric Calibration and Accuracy Evaluation of Smartphone Camera (스마트폰 카메라의 기하학적 검정과 정확도 평가)

  • Kim, Jin-Soo;Jin, Cheong-Gil;Lee, Seong-Kyu;Lee, Sun-Gu;Choi, Chul-Uong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.3
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    • pp.115-125
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    • 2011
  • The smartphones which have been recently are embedded with high resolution quality camera, assisted GPS, accelerometer, gyroscope and various sensors including magnetometer sensor that could be directly used for measurement. This study aims to suggest the possible application of smartphone camera providing high resolution images in terms of photogrammetry by calibrating it and assessing its accuracy. First of all, prior to the accuracy assessment of smartphone camera, camera calibration was conducted to correct lens distortion of each camera and the accuracy of image coordinates and object coordinates calculated by bundle adjustment during this procedure was analyzed. Also regarding three-dimensional positioning, result analysis depending on considering lens distortion coefficients was conducted, and finally relative accuracy of smartphone camera on metric camera was assessed. The result showed that in terms of distortion correction of smartphone camera, also higher order symmetric radial lens distortion coefficients should be considered, and three dimensional position determined by smartphone images was a little difference from that by metric camera. Therefore it is expected that smartphone images have huge possibility to be used for photogrammetry.

3D Rigid Body Tracking Algorithm Using 2D Passive Marker Image (2D 패시브마커 영상을 이용한 3차원 리지드 바디 추적 알고리즘)

  • Park, Byung-Seo;Kim, Dong-Wook;Seo, Young-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.587-588
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    • 2022
  • In this paper, we propose a rigid body tracking method in 3D space using 2D passive marker images from multiple motion capture cameras. First, a calibration process using a chess board is performed to obtain the internal variables of individual cameras, and in the second calibration process, the triangular structure with three markers is moved so that all cameras can observe it, and then the accumulated data for each frame is calculated. Correction and update of relative position information between cameras. After that, the three-dimensional coordinates of the three markers were restored through the process of converting the coordinate system of each camera into the 3D world coordinate system, the distance between each marker was calculated, and the difference with the actual distance was compared. As a result, an error within an average of 2mm was measured.

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Gravity Survey Around the Palgongsan Granitic Body and Its Vicinity (팔공산화강암체와 그 인근지역에서의 중력탐사 연구)

  • Hwang, Jong-Sun;Min, Kyung-Duck;Choi, Chul;Yu, Sang-Hoon
    • Economic and Environmental Geology
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    • v.36 no.4
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    • pp.305-312
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    • 2003
  • This study was performed to delineate the subsurface geology, geologic structure, and distribution pattern of the Palgongsan granitic body, and to reveal the relationship between the Kyeongsang basin and Yongnam massif by gravity survey. The study area is located between the latitude of 35$^{\circ}$45'-36$^{\circ}$21'N and longitude of 128$^{\circ}$15'-129$^{\circ}$00'E. Total of 966 gravity data measured by Seoul National University, KlGAM(Korea Institute of Geology, Mining & Materials), Pusan National University and Yonsei University were used. The Bouguer gravity anomaly in the study area ranges from -12.88 to 26.01 mgal with a mean value of 11.27 mgal. A very low anomaly zone is located in the Yongnam massif in west of the study area. The anomaly value increases going from west to east. A low anomaly distribution in Palgongsan granite and Yongnam massif is interpreted as the effect of their lower density than that of Kyeongsang Super Group. Power spectrum analysis is applied to evaluate the average depth of basement the Kyeongsang Basin and Conrad discontinuity from gravity anomaly. The average depths of density discontinuities are calculated 10.45 km and 4.9 km, and these are interpreted as Conrad discontinuity and depth of basement of the Kyeongsang Basin, respectively. The depth of Palgongsan granite is derived by means of 2-dimensional modeling and it decreases gradually toward the east. The gravity anomaly east of the study area decreases abruptly due to Shingryeong fault and Nogosan ring fault. Two deepest and sharp roots of Palgongsan granite are recognized by 2-dimensional modeling of each profiles. The depths of those roots are 5.3 km on a profile AA' and 7 km on a profile BB' which is the maximum depth of Palgongsan granite. Small granitic bodies are also seen to be intruded around the Palgongsan granite. The root of Palgongsan granite is shown by 3-dimensional analysis based on the interpolation of 2-dimensional modeling along each profiles to exist in the southwest vicinity of Palgongsan granite. The total volume of Palgongsan granite is approximately 31.211 $Km^3$.

Positioning Method Using a Vehicular Black-Box Camera and a 2D Barcode in an Indoor Parking Lot (스마트폰 카메라와 2차원 바코드를 이용한 실내 주차장 내 측위 방법)

  • Song, Jihyun;Lee, Jae-sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.1
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    • pp.142-152
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    • 2016
  • GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

Updating Building Layer of Digital Map Using Airborne Digital Camera Image (디지털항공영상을 이용한 수치지도의 건물레이어 갱신)

  • Hwang, Won-Soon;Kim, Kam-Rae
    • Journal of Korean Society for Geospatial Information Science
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    • v.15 no.4
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    • pp.31-39
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    • 2007
  • As the availability of images from airborne digital camera with high resolution is expanded, a lot of concern are shown about the production of orthoimage and digital map. This study presents the method of updating digital map using orthoimage from airborne digital camera image. Images were georectified using GPS surveying data. For the generation of orthoimage, Lidar DEM was used. The absolute positional accuracy of orthoimage was evaluated using GPS surveying data. And that of the building layer of digital map was estimated using the existed digital map at the scale of 1:1,000. The absolute positional accuracy of orthoimage was as followed: RMSE in X and Y were ${\pm}0.076m$ and ${\pm}0.294m$. The RMSE of the building layer were ${\pm}0.250m$ and ${\pm}0.210m$ in X and Y directions, respectively. The RMSE of the digital map using orthoimage from Aerial Digital Camera image fell within allowable error range established by NGII. Consequently, updating digital map using orthoimage from Aerial Digital Camera image can be applied to various fields including the construction of the framework data and the GIS of local government.

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Performance Analysis of Vision-based Positioning Assistance Algorithm (비전 기반 측위 보조 알고리즘의 성능 분석)

  • Park, Jong Soo;Lee, Yong;Kwon, Jay Hyoun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.3
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    • pp.101-108
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    • 2019
  • Due to recent improvements in computer processing speed and image processing technology, researches are being actively carried out to combine information from camera with existing GNSS (Global Navigation Satellite System) and dead reckoning. In this study, developed a vision-based positioning assistant algorithm to estimate the distance to the object from stereo images. In addition, GNSS/on-board vehicle sensor/vision based positioning algorithm is developed by combining vision based positioning algorithm with existing positioning algorithm. For the performance analysis, the velocity calculated from the actual driving test was used for the navigation solution correction, simulation tests were performed to analyse the effects of velocity precision. As a result of analysis, it is confirmed that about 4% of position accuracy is improved when vision information is added compared to existing GNSS/on-board based positioning algorithm.

Validation of the Complementary Relationship of Evapotranspiration Hypothesis Using In-situ Measurements (관측자료 기반의 용담댐 유역 증발산 보완관계 가설 검증)

  • Eunji Kim;Boosik Kang
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.264-264
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    • 2023
  • 물순환 과정에서의 증발산은 장기적인 관점에서의 수자원 계획 수립 시 중요한 요소이다. 증발산은 기온, 상대습도, 일사량 등 기상학적 인자뿐만 아니라 증발표면, 식생분포 등 다양한 인자의 복합작용에 의해 일어나므로, 유역 단위에서 발생한 실제증발산(Actual evapotranspiration, AET)을 측정하기에는 기술적인 한계가 존재한다. 그러나 증발산 보완관계(Complementary relationship of evapotranspiration, CRE) 가설을 활용하면, 수문요소의 상호작용을 고려한 모델링을 거치지 않고도, 비교적 간단하게 AET를 추정할 수 있다. 본 연구는 증발산 관측자료를 기반으로 유역 단위에서의 CRE를 검증하고자 하며, 플럭스 타워 등 다양한 관측장비가 설치되어 있는 용담댐 시험유역을 대상유역으로 선정하였다. 용담댐 유역 내 산지에 위치한 덕유산 플럭스 타워에서 측정된 증발산을 AET로 보았으며, 유역 인근에 위치한 전주 기상관측소에서 측정되는 팬 증발량(Epan)을 잠재증발산량(Potential evapotranspiration, PET)으로 보았다. Epan 계측시, 증발팬의 가열 등 주변환경 변화로 인해 과다하게 추정되는 값을 보완하기 위해 FAO Penman-Monteith 식을 활용해 팬 증발량 보정계수(Coefficient of pan evaporation, kp)를 산정하여 적용하였다. 습윤증발산량(Wet evapotranspiration, WET)은 대기가 완전히 포화되었을 때 발생하는 증발산량으로, 댐 수표면에서 계측되는 수면증발량을 WET로 보았다. CRE 검증을 위해 AET와 PET를 각각 WET로 나누어 AET+와 PET+로 무차원화하였으며, 습윤지수(Moisture Index, MI)는 AET를 PET로 나누어 산정하였다. CRE 가설은 MI에 따른 AET+와 PET+가 서로 보완관계를 갖는다는 것인데, 용담댐 유역의 관측자료를 활용하여 CRE를 검증한 결과 AET+와 PET+ 간의 비대칭계수(b)가 1.23인 것으로 나타났다. 이 때의 평균제곱오차(MSE)는 0.599, 결정계수(R2)는 0.631로 나타나 CRE의 b가 적합하게 추정된 것으로 판단된다. 본 연구결과와 같이 검증된 CRE를 통해 증발산 관측지점이 없거나, 조밀하지 않은 유역의 AET를 간접추정할 수 있으며, 이를 활용해 보다 정확한 댐의 장기유출 모의와 용수공급계획 수립에 도움을 줄 수 있을 것으로 기대된다.

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Development of Biotelemetry Method by Combining the SSBL Method and the Pinger Synchronizing Method (1) - Design and production of system - (SSBL 방식과 핑거동기 방식을 조합한 바이오텔레메터리 방식의 개발 (1) -시스템의 설계 및 제작 -)

  • 박주삼;고탁창언
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.39 no.3
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    • pp.218-229
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    • 2003
  • A new biotelemetry method that the installation and the treatment of equipment is convenient and the instantaneously detailed location of the fish attached the pinger is able to track comparatively easily was developed. The receiving system in this biotelemetry method was advanced for track the detailed behavior of the fish by the miniature tracking pinger, because it was a burden to fish to add the pinger with the water temperature and the pressure sensor. By combining of the super short base line (SSBL) method to detect the direction of pinger and the pinger synchronizing method to measure the range from receiving transducer to pinger, the three dimensional locations of fish to the receiving transducer is gotten instantaneously. The receiving system is devised to realize the high precision or wide detection range by application of the basic design method for receiving system of biotelemetry developed by the present authors and the hydrophone array configuration. The measurement distance error in the pinger synchronizing method is minimized through the correction of which the deviation of transmission pluse period of pinger is caused by changing water temperature. A prototype system which is able to track the instantaneously detailed location of the fish by the SSBL and pinger synchronizing biotelemetry (SPB) method was produced.

Generation of Grid Maps of GPS Signal Delays in the Troposphere and Analysis of Relative Point Positioning Accuracy Enhancement (GPS 신호의 대류권 지연정보 격자지도 생성과 상대측위 정확도 향상 평가)

  • Kim, Dusik;Won, Jihye;Son, Eun-Seong;Park, Kwan-Dong
    • Journal of Navigation and Port Research
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    • v.36 no.10
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    • pp.825-832
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    • 2012
  • GPS signal delay that caused by dry gases and water vapor in troposphere is a main error source of GPS point positioning and it must be eliminated for precise point positioning. In this paper, we implemented to generate tropospheric delay grid map over the Korean Peninsula based on post-processing method by using the GPS permanent station network in order to determine the availability of tropospheric delay generation algorithm. GIPSY 5.0 was used for GPS data process and nationwide AWS observation network was used to calculate the amount of dry delay and wet delay separately. As the result of grid map's accuracy analysis, the RMSE between grid map data and GPS site data was 0.7mm in ZHD, 7.6mm in ZWD and 8.5mm in ZTD. After grid map accuracy analysis, we applied the calculated tropospheric delay grid map to single frequency relative positioning algorithm and analyzed the positioning accuracy enhancement. As the result, positioning accuracy was improved up to 36% in case of relative positioning of Suwon(SUWN) and Mokpo(MKPO), that the baseline distance is about 297km.

KOMPSAT Optical Image Registration via Deep-Learning Based OffsetNet Model (딥러닝 기반 OffsetNet 모델을 통한 KOMPSAT 광학 영상 정합)

  • Jin-Woo Yu;Che-Won Park;Hyung-Sup Jung
    • Korean Journal of Remote Sensing
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    • v.39 no.6_3
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    • pp.1707-1720
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    • 2023
  • With the increase in satellite time series data, the utility of remote sensing data is growing. In the analysis of time series data, the relative positional accuracy between images has a significant impact on the results, making image registration essential for correction. In recent years, research on image registration has been increasing by applying deep learning, which outperforms existing image registration algorithms. To train deep learning-based registration models, a large number of image pairs are required. Additionally, creating a correlation map between the data of existing deep learning models and applying additional computations to extract registration points is inefficient. To overcome these drawbacks, this study developed a data augmentation technique for training image registration models and applied it to OffsetNet, a registration model that predicts the offset amount itself, to perform image registration for KOMSAT-2, -3, and -3A. The results of the model training showed that OffsetNet accurately predicted the offset amount for the test data, enabling effective registration of the master and slave images.