References
- Abayowa, B.O., Yilmaz, A., and Hardie, R.C. (2015), Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 106, pp. 68-81. https://doi.org/10.1016/j.isprsjprs.2015.05.006
- Abedini, A., Hahn, M., and Samadzadegan, F. (2008), An investigation into the registration of LiDAR intensity data and aerial images using the SIFT approach, In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, pp. 169-176.
- Alcantarilla, P.F., Bartoli, A., and Davison, A.J. (2012), KAZE features, In European Conference on Computer Vision, Springer, Berlin, Heidelberg, pp. 214-227.
- Bohm, J. and Becker, S. (2007), Automatic marker-free registration of terrestrial laser scans using reflectance, In Proceedings of the 8th Conference on Optical 3D Measurement Techniques, Zurich, Switzerland, pp. 9-12.
- Commercializations Promotion Agency for R&D Outcomes (COMPA), (2017), LiDAR Technology and Market Trends, S&T Market Report, Vol. 54, 16p. (in Korean)
- Conte, G. and Doherty, P. (2008), An integrated UAV navigation system based on aerial image matching, In 2008 IEEE Aerospace Conference, IEEE, pp. 1-10.
- Fernandez, J.C., Singhania, A., Caceres, J., Slatton, K.C., Starek, M., and Kumar, R. (2007), An Overview of Lidar Point Cloud Processing Software, GEM Center Report No. Rep_2007-12-001, University of Florida, 27p.
- Fischler, M.A. and Bolles, R.C. (1981), Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, Vol. 24, No. 6, pp. 381-395. https://doi.org/10.1145/358669.358692
- Guan, H., Li, J., Yu, Y., Wang, C., Chapman, M., and Yang, B. (2014). Using mobile laser scanning data for automated extraction of road markings, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 87, pp. 93-107. https://doi.org/10.1016/j.isprsjprs.2013.11.005
- Harris, C.G. and Stephens, M. (1988), A combined corner and edge detector. In Alvey Vision Conference, Vol. 15, No. 50, pp. 10-5244.
- Hong, S., Park, I., Lee, J., Lim, K., Choi, Y., and Sohn, H.G. (2017), Utilization of a terrestrial laser scanner for the calibration of mobile mapping systems, Sensors, Vol. 17, No. 3, 24p.
- Kim, T. and Im, Y.J. (2003), Automatic satellite image registration by combination of matching and random sample consensus, IEEE transactions on geoscience and remote sensing, Vol. 41, No. 5, pp. 1111-1117. https://doi.org/10.1109/TGRS.2003.811994
- Kim, M. (2005), The Study on Road Extraction Using LiDAR Data, Master's thesis, Inha University, Incheon, Korea, 62p. (in Korean with English abstract)
- Kim, S., Yoo, H., and Sohn, K. (2012), FAST and BRIEF based real-time feature matching algorithms, In Proceedings of the Korean Society of Broadcast Engineers Conference, pp. 1-4. (in Korean)
- Li, Q., Wang, G., Liu, J., and Chen, S. (2009), Robust scaleinvariant feature matching for remote sensing image registration, IEEE Geoscience and Remote Sensing Letters, Vol. 6, No. 2, pp. 287-291. https://doi.org/10.1109/LGRS.2008.2011751
- Lindeberg, T. (2015), Image matching using generalized scalespace interest points, Journal of Mathematical Imaging and Vision, Vol. 52, No. 1, pp. 3-36. https://doi.org/10.1007/s10851-014-0541-0
- Liu, S., Tong, X., Chen, J., Liu, X., Sun, W., Xie, H., Chen, P., Jin, Y., and Ye, Z. (2016), A linear feature-based approach for the registration of unmanned aerial vehicle remotely-sensed images and airborne LiDAR data, Remote Sensing, Vol. 8, No. 2, 15p.
- Lowe, D. (2004), Distinctive image features from scaleinvariant keypoints, International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110. https://doi.org/10.1023/B:VISI.0000029664.99615.94
- Matas, J., Chum, O., Urban, M., and Pajdla, T. (2004), Robust wide-baseline stereo from maximally stable extremal regions, Image and Vision Computing, Vol. 22, pp. 761-767. https://doi.org/10.1016/j.imavis.2004.02.006
- Mikolajczyk, K. and Schmid, C. (2005), A performance evaluation of local descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, pp. 1615-1630. https://doi.org/10.1109/TPAMI.2005.188
- Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., and Van Gool, L. (2005), A Comparison of Affine Region Detectors, International Journal of Computer Vision, Vol. 65, pp. 43-72. https://doi.org/10.1007/s11263-005-3848-x
- Miksik, O. and Mikolajczyk, K. (2012), Evaluation of local detectors and descriptors for fast feature matching, In Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), IEEE, pp. 2681-2684.
- Moravec, H. (1980), Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover, No. STAN-CS-80-813, Stanford University, California, USA.
- Nho, H. (2018), Fast Geocoding Processing for Low-cost Unmanned Aerial Vehicle Imagery, Master's thesis, Yonsei University, Seoul, Korea, 69p.
- Palenichka, R.M. and Zaremba, M.B. (2010), Automatic extraction of control points for the registration of optical satellite and LiDAR images, IEEE Transactions on Geoscience and Remote sensing, Vol. 48, No. 7, pp. 2864-2879. https://doi.org/10.1109/TGRS.2010.2043677
- Park, S., Kim, J., and Yoo, J. (2015), Fast stitching algorithm by using feature tracking, Journal of Broadcast Engineering, Vol. 20, No. 5, pp. 728-737. (in Korean with English abstract) https://doi.org/10.5909/JBE.2015.20.5.728
- Park, J., Kim, P., Cho, Y.K., and Kang, J. (2019), Framework for automated registration of UAV and UGV point clouds using local features in images, Automation in Construction, Vol. 98, pp. 175-182. https://doi.org/10.1016/j.autcon.2018.11.024
- Peng, W.H., Lee, M.Y., Li, T.H., Huang, C.H., and Lin, P.C. (2016), Performance comparison of image keypoint detection, description, and matching methods, In 2016 IEEE 5th Global Conference on Consumer Electronics, IEEE, pp. 1-2.
- Persad, R.A. and Armenakis, C. (2016), Co-registration of DSMs generated by UAV and terrestrial laser scanning systems, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B1, pp. 985-990. https://doi.org/10.5194/isprs-archives-XLI-B1-985-2016
- Rosten, E. and Drummond, T. (2006), Machine learning for high speed corner detection, In 9th Euproean Conference on Computer Vision, Vol. 1, pp. 430-443.
- Schmind, C., Mohr, R., and Bauckhage, C. (2000), Evaluation of interest point detectors, International Journal of Computer Vision, Vol. 37, No. 2, pp. 151-172. https://doi.org/10.1023/A:1008199403446
- Shi, J. and Tomasi, C. (1994), Good Features to Track, CVPR.
- Tareen, S.A.K. and Saleem, Z. (2018), A comparative analysis of sift, surf, kaze, akaze, orb, and brisk, In 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, pp. 1-10.
- Tsai, C.H. and Lin, Y.C. (2017), An accelerated image matching technique for UAV orthoimage registration, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 128, pp. 130-145. https://doi.org/10.1016/j.isprsjprs.2017.03.017
- Vedaldi, A. and Fulkerson, B. (2010), VLfeat: An open and portable library of computer vision algorithms, In Proceedings of the 18th ACM international conference on Multimedia, Firenze, Italy, pp. 25-29.
- Verma, S.B. and Chandran, S. (2016), Comparative Study of FAST MSER and Harris for Palmprint Verification System, International Journal of Scientific & Engineering Research, Vol. 7, No. 12, pp. 855-858.
- Yang, B. and Chen, C. (2015), Automatic registration of UAVborne sequent images and LiDAR data, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 101, pp. 262-274. https://doi.org/10.1016/j.isprsjprs.2014.12.025