03-16-김용일.indd

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1 Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography Vol. 33, No. 2, , ISSN (Print) ISSN X(Online) Original article 시뮬레이션을통한광학및레인지센서간의효율적인시스템캘리브레이션설계 A Study for Efficient Methods of System Calibration between Optical and Range Sensors by Using Simulation 최원석 1) 김창재 2) 김용일 3) Choi, Won Seok Kim, Chang Jae Kim, Yong Il Abstract The study planned to suggest the efficient methods of system calibration between the range and optical sensors. The simulation was performed by considering i) design of test-bed, ii) mathematical methods of system calibration and iii) locations of the sensors. The test-bed was designed by considering specifications of the range and optical sensors. Also, the error levels of each sensor were considered in the process of simulation with dataset, which was generated under these predetermined conditions. The system calibration was carried out by using the simulated dataset in two different approaches, which are single photo resection and bundle adjustment. The results from the simulation determined that the bundle adjustment method is more efficient than the single photo resection in the system calibration between range and optical sensors. For the better results, we have used the data, obtained in various locations. In a conclusion, the most efficient case was in sequence of i) the bundle adjustment with ii) the simulated dataset, which were obtained between 2m to 4m away from the test-bed. Keywords : System Calibration, Range Sensor, Optical Sensor, Test-bed, 3D Data Fusion 초록.,..,., 2~4m,.. :,,,, 3 Received , Revised , Accepted ) Department of Civil and Environmental Engineering, Seoul National University ( youn0603@snu.ac.kr) 2) Member, Myongji University, Department of Civil and Environmental Engineering( cjkim@mju.ac.kr) 3) Corresponding Author, Member, Department of Civil and Environmental Engineering, Seoul National University ( yik@snu.ac.kr) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 95

2 Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 33, No. 2, , 서론 3. 3, BIM. 3,. 3,., (System Calibration). (Habib et al., 2002; Habib et al., 2003; Habib and Morgan, 2005; Kim et al., 2011; Lee et al., 2010; Oh et al., 2006)., 3 (Choi and Sohn, 2011; Kang and Ho, 2011)., 3.,. TOF(Time of Flight)., (Lichti and Kim, 2011).,.,,.,.,. 2. 연구방법 Fig. 1,,., MATLAB. i), ii) iii). Fig. 1. Flow chart of system calibration simulation 2.1 검정대상지설계 m 96

3 A Study for Efficient Methods of System Calibration between Optical and Range Sensors by Using Simulation, (Fig. 2).. 3, 0m(design 1), 0.25m(design 2), 0.5m(design 3) (Fig. 3). Lichti et al.(2010).. Fig. 4 Matlab,. Fig. 2. Test-bed design for system calibration between optical and range sensors (diamond shape: points which are not given changing in height / circle shape : points which are given changing in height) Fig. 4. Simulated control points on the range sensor test-bed 2.2 센서의제원및가상의내부표정요소결정. Canon 6D EF 35mm f/2 IS USM, MESA Imaging SR4000. Table 1 Table 2. Table 3 Table 4. Table 1. Specification of Cannon 6D camera sensor pixel size mm(size L) image size pixel Table 2. Specification of SR4000 range sensor Fig. 3. Simulated control points on the optical sensor test-bed (top to bottom design1, design2, design3) distance accuracy image size pixel size focal length 15mm 176(h)144(v) mm 97

4 Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 33, No. 2, , 2015 Table 3. Interior orientation parameters of optical and range sensors x coordinates of principle point(mm) y coordinates of principle point(mm) focal length(mm) optical sensor range sensor Table 4. Distortion parameters of optical and range sensors optical sensor range sensor coefficient value coefficient value coefficient value k1-3.30e-04 k1-7.81e-03 d k2 0 k2-2.72e-04 d1-d7 0 k3 0 k3 0 e1-e11 0 p1 0 p1-1.15e-04 U p2 0 p2-2.87e-04 a1 0 a1 0 a2 0 a 외부및상대표정요소설정및시뮬레이션영상제작 Fig m Y, 6. (ROP, Relative Orientation Parameters) Table 5. Fig. 6. Fig. 6, 21.,., (Eq. (1) Eq. (2)). Fig. 5. Relative location between optical and range sensors Table 5. Relative orientation parameters of range sensor X rop (m) Y rop (m) Z rop (m) ω rop φ rop κ rop Fig. 6. Shooting locations of optical and range sensors (circles : location of optical sensor / squares : location of range sensor) 98

5 A Study for Efficient Methods of System Calibration between Optical and Range Sensors by Using Simulation, Eq. (1) Eq. (2), Eq. (3).,, 0, 1. (1) where image x, coordinates y: image coordinates of sensor of data, sensor data, x, y: distortions of image coordinates, x p, y p : principal points of image data, f: focal length, m 11 ~m 33 : components of rotation matrix, X, Y, Z: ground coordinates of control points, X 0, Y 0, Z 0 : exterior orientation parameters of sensor(shooting location), ρ: range value(measured distance value), and ρ: distortion of range value 2.4 단사진표정및블록조정을통한시스템캘리브레이션,., (iteration method) (2) (3)..,,.,. 3. 연구결과 Table 6, Table 7.. Fig. 7.,.. Y 0. Y Y 0,,. (Fig. 3 )., Table 6. Results of system calibration using single photo resection used data design of test bed X 0 (m) Y 0 (m) Z 0 (m) ω φ κ design image design design design image + range design design true value

6 Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 33, No. 2, , 2015 used data image image + range design of test bed Table 7. Results of system calibration using bundle adjustment X 0 (m) Y 0 (m) Z 0 (m) ω φ κ design design design design design design true value ,. Fig. 8 ( ). 2m, 2~3m, 2~4m. (a) (b) (c) (d) (a) (e) (f) Fig. 8. Trends of relative orientation parameters errors while increasing the number of images 4. 결론 (b) Fig. 7. Comparison of relative orientation parameters errors ((a) X0, Y0, Z0 / (b) ω, Φ, κ),., 100

7 A Study for Efficient Methods of System Calibration between Optical and Range Sensors by Using Simulation. i),. ii),. iii) 2~4m,..,.,. 감사의글 (:NRF -2012R1A1A ). References of Electronics Engineers of Korea, Vol. 48, No. 3, pp (in Korean with English abstract) Kim, C., Sohn, H., Heo, J., and Lichti, D. (2011), 3D range camera calibration, 2011 Conference on Geospatial Information, Korean society for geospatial information system, May, Korea, pp (in Korean) Lee, C., Kim, C., and Seo, S. (2010), Platform calibration of an aerial multi-view camera system, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 28, No. 3, pp (in Korean with English abstract) Lichti, D.D. and Kim, C. (2011), A comparison of three geometric self-calibration methods for range cameras, Remote Sensing, Vol. 28, No. 5, pp Lichti, D.D., Kim, C., and Jamtsho, S. (2010), An integrated bundle adjustment approach to range camera geometric self-calibration, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 65, Issue 4, pp Oh, J., Lee, C., and Eo, Y. (2006), A photogrammetric network and object field design for efficient selfcalibration of non-metric digital cameras, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 24, No. 3, pp (in Korean with English abstract) Choi, J. and Sohn, K. (2011), Multi-view depth image resolution enhancement based on view coherence, 2011 Conference of The Korean Society of Broadcast Engineers, The Korean Society of Broadcast Engineers, July, Korea, pp (in Korean) Habib, A.F. and Morgan, M. (2005), Stability analysis and geometric calibration of off-the-shelf digital cameras, Photogrammetric Engineering and Remote Sensing, Vol. 71, No. 6, pp Habib, A.F., Morgan, M., and Lee, Y. (2002), Bundle adjustment with self-calibration using straight lines, The Photogrammetric Record, Vol. 17, No. 100, pp Habib, A.F. and Morgan, F.M. (2003), Automatic calibration of low-cost digital cameras, Optical Engineering, Vol. 42, No.4, pp Kang, Y. and Ho, Y. (2011), Depth generation method using multiple color and depth cameras, Journal of the Institute 101

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