{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:02:02Z","timestamp":1775836922520,"version":"3.50.1"},"reference-count":78,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,8,30]],"date-time":"2017-08-30T00:00:00Z","timestamp":1504051200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.<\/jats:p>","DOI":"10.3390\/s17091987","type":"journal-article","created":{"date-parts":[[2017,8,30]],"date-time":"2017-08-30T10:40:00Z","timestamp":1504089600000},"page":"1987","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor"],"prefix":"10.3390","volume":"17","author":[{"given":"Phong Ha","family":"Nguyen","sequence":"first","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Ki Wan","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Young Won","family":"Lee","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Kang Ryoung","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,30]]},"reference":[{"key":"ref_1","unstructured":"(2017, April 17). Commercial UAV Market Analysis by Product (Fixed Wing, Rotary Blade, Nano, Hybrid), by Application (Agriculture, Energy, Government, Media & Entertainment) and Segment Forecasts to 2022. Available online: http:\/\/www.grandviewresearch.com\/industry-analysis\/commercial-uav-market."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Austin, R. (2010). Unmanned Aircraft Systems: Uavs Design, Development and Deployment, John Wiley & Sons.","DOI":"10.1002\/9780470664797"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40327-015-0029-z","article-title":"Visual monitoring of civil infrastructure systems via camera-equipped unmanned aerial vehicles (UAVs): A review of related works","volume":"4","author":"Ham","year":"2016","journal-title":"Vis. Eng."},{"key":"ref_4","first-page":"283","article-title":"Towards UAV-based bridge inspection systems: A review and an application perspective","volume":"2","author":"Chan","year":"2015","journal-title":"Struct. Monit. Maint."},{"key":"ref_5","first-page":"125","article-title":"High-resolution multisensor infrastructure inspection with unmanned aircraft systems. Int. Arch. Photogramm","volume":"2","author":"Eschmann","year":"2013","journal-title":"Remote Sens. Spat. Inf. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"14887","DOI":"10.3390\/s150714887","article-title":"Vision and control for UAVs: A survey of general methods and of inexpensive platforms for infrastructure inspection","volume":"15","year":"2015","journal-title":"Sensors"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Valavanis, K.P., and Vachtsevanos, G.J. (2015). Inertial sensor\u2013based simultaneous localization and mapping for UAVs. Handbook of Unmanned Aerial Vehicles, Springer.","DOI":"10.1007\/978-90-481-9707-1"},{"key":"ref_8","unstructured":"Feldman, M.S. (2014). Simultaneous Localization and Mapping Implementations for Navigation of an Autonomous Robot. [Bachelor\u2019s Thesis, Department of Electrical and Computer Engineering]."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1177\/0142331214565964","article-title":"SLAM\u2013inspired simultaneous localization of UAV and RF sources with unknown transmitted power","volume":"38","author":"Dehghan","year":"2016","journal-title":"Trans. Inst. Meas. Control"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s10846-011-9587-z","article-title":"Obstacle avoidance for unmanned aerial vehicles","volume":"65","author":"Cruz","year":"2012","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1109\/ACCESS.2015.2432455","article-title":"Obstacle detection and collision avoidance for a UAV with complementary low\u2013cost sensors","volume":"3","author":"Gageik","year":"2015","journal-title":"IEEE Access."},{"key":"ref_12","unstructured":"Call, B.R. (2006). Obstacle Avoidance for Small Unmanned Air Vehicles. [Master\u2019s Thesis, Brigham Young University]."},{"key":"ref_13","unstructured":"Barry, A.J. (2016). High\u2013Speed Autonomous Obstacle Avoidance with Pushbroom Stereo. [Ph.D. Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology]."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"29734","DOI":"10.3390\/s151129734","article-title":"UAVs task and motion planning in the presence of obstacles and prioritized targets","volume":"15","author":"Gottlieb","year":"2015","journal-title":"Sensors"},{"key":"ref_15","unstructured":"Partsinevelos, P., Agadakos, I., Athanasiou, V., Papaefstathiou, I., Mertikas, S., Kyritsis, S., Tripolitsiotis, A., and Zervos, P. (May, January 27). On\u2013board computational efficiency in real time UAV embedded terrain reconstruction. Proceedings of the the European Geosciences Union General Assembly, Vienna, Austria."},{"key":"ref_16","first-page":"75","article-title":"Context\u2013based urban terrain reconstruction from UAV\u2013videos for geoinformation applications","volume":"22","author":"Bulatov","year":"2011","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inform. Sci."},{"key":"ref_17","first-page":"1","article-title":"Real\u2013time monitoring system using unmanned aerial vehicle integrated with sensor observation service","volume":"22","author":"Witayangkurn","year":"2011","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inform. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2012\/858792","article-title":"UAV\u2013based sensor web monitoring system","volume":"2012","author":"Nagai","year":"2012","journal-title":"Int. J. Navig. Observ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1007\/978-3-642-39649-6_11","article-title":"Development of a software to plan UAVs stereoscopic flight: An application on post earthquake scenario in L\u2019Aquila city","volume":"7974","author":"Baiocchi","year":"2013","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_20","first-page":"396","article-title":"A review on marine search and rescue operations using unmanned aerial vehicles","volume":"9","author":"Yeong","year":"2015","journal-title":"Int. J. Mech. Aerosp. Ind. Mech. Manuf. Eng."},{"key":"ref_21","unstructured":"(2017, April 17). Amazon Prime Air. Available online: https:\/\/www.amazon.com\/Amazon\u2013Prime\u2013Air\/b?node=8037720011."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, C., Campoy, P., Mondrag\u00f3n, I., and Olivares\u2013M\u00e9ndez, M.A. (2009, January 10\u201315). Trinocular ground system to control UAVs. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA.","DOI":"10.1109\/IROS.2009.5354489"},{"key":"ref_23","unstructured":"Kong, W., Zhang, D., Wang, X., Xian, Z., and Zhang, J. (2013, January 3\u20137). Autonomous landing of an UAV with a ground\u2013based actuated infrared stereo vision system. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/s16091393","article-title":"A ground\u2013based near infrared camera array system for UAV auto\u2013landing in GPS\u2013denied environment","volume":"16","author":"Yang","year":"2016","journal-title":"Sensors"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2250","DOI":"10.1016\/j.proeng.2012.06.271","article-title":"Vision based autonomous landing of an unmanned aerial vehicle","volume":"38","author":"Anitha","year":"2012","journal-title":"Procedia Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.aasri.2013.10.035","article-title":"A software scheme for UAV\u2019s safe landing area discovery","volume":"4","author":"Li","year":"2013","journal-title":"AASRI Procedia"},{"key":"ref_27","unstructured":"Sharp, C.S., Shakernia, O., and Sastry, S.S. (2001, January 21\u201326). A vision system for landing an unmanned aerial vehicle. Proceedings of the the IEEE International Conference on Robotics and Automation, Seoul, Korea."},{"key":"ref_28","unstructured":"Lange, S., S\u00fcnderhauf, N., and Protzel, P. (2008, January 3\u20134). Autonomous landing for a multirotor UAV using vision. Proceedings of the the International Conference on Simulation, Modeling and Programming for Autonomous Robots, Venice, Italy."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1016\/j.phpro.2012.05.157","article-title":"An improved vision\u2013based algorithm for unmanned aerial vehicles autonomous landing","volume":"33","author":"Zhao","year":"2012","journal-title":"Phys. Procedia"},{"key":"ref_30","first-page":"23","article-title":"NEEC research: Toward GPS\u2013denied landing of unmanned aerial vehicles on ships at sea","volume":"127","author":"Chaves","year":"2015","journal-title":"Nav. Eng. J."},{"key":"ref_31","unstructured":"Ling, K. (2014). Precision Landing of a Quadrotor UAV on a Moving Target Using Low\u2013Cost Sensors. [Master\u2019s Thesis, University of Waterloo]."},{"key":"ref_32","unstructured":"(2017, April 17). AprilTag. Available online: https:\/\/april.eecs.umich.edu\/software\/apriltag.html."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Kyristsis, S., Antonopoulos, A., Chanialakis, T., Stefanakis, E., Linardos, C., Tripolitsiotis, A., and Partsinevelos, P. (2016). Towards autonomous modular UAV missions: The detection, geo\u2013location and landing paradigm. Sensors, 16.","DOI":"10.3390\/s16111844"},{"key":"ref_34","unstructured":"(2017, April 17). AprilTags C++ Library. Available online: http:\/\/people.csail.mit.edu\/kaess\/apriltags\/."},{"key":"ref_35","unstructured":"(2017, April 17). Linux for Tegra R27.1. Available online: https:\/\/developer.nvidia.com\/embedded\/linux\u2013tegra."},{"key":"ref_36","unstructured":"(2017, April 27). DJI. Available online: http:\/\/www.dji.com."},{"key":"ref_37","unstructured":"(2017, April 27). Jetson TK1. Available online: http:\/\/www.nvidia.com\/object\/jetson\u2013tk1\u2013embedded\u2013dev\u2013kit.html."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1016\/j.patrec.2008.12.011","article-title":"Research on computer vision\u2013based for UAV autonomous landing on a ship","volume":"30","author":"Xu","year":"2009","journal-title":"Pattern Recognit. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1016\/j.cja.2013.07.049","article-title":"Use of land\u2019s cooperative object to estimate UAV\u2019s pose for autonomous landing","volume":"26","author":"Xu","year":"2013","journal-title":"Chin. J. Aeronaut."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Babenko, B., Yang, M.H., and Belongie, S. (2009, January 20\u201326). Visual tracking with online multiple instance learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206737"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1109\/TPAMI.2011.239","article-title":"Tracking\u2013learning\u2013detection","volume":"34","author":"Kalal","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Kalal, Z., Mikolajczyk, K., and Matas, J. (2010, January 23\u201326). Forward\u2013backward error: Automatic detection of tracking failures. Proceedings of the International Conference on Pattern Recognition, Istanbul, Turkey.","DOI":"10.1109\/ICPR.2010.675"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1109\/TPAMI.2014.2345390","article-title":"High\u2013speed tracking with kernelized correlation filters","volume":"37","author":"Henriques","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded\u2013up robust features (SURF)","volume":"110","author":"Bay","year":"2006","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale\u2013invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Calonder, M., Lepetit, V., Strecha, C., and Fua, P. (2010, January 5\u201311). Brief: Binary robust independent elementary features. Proceedings of the European Conference on Computer Vision, Heraklion, Greece.","DOI":"10.1007\/978-3-642-15561-1_56"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., and Bradski, G. (2011, January 6\u201313). ORB: An efficient alternative to SIFT or SURF. Proceedings of the IEEE International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_48","unstructured":"(2017, August 03). MUTOH Printer. Available online: https:\/\/www.mutoh.eu\/."},{"key":"ref_49","first-page":"2659","article-title":"A study on similarity computations in template matching technique for identity verification","volume":"2","author":"Lam","year":"2010","journal-title":"Int. J. Comput. Sci. Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.1016\/j.patrec.2009.12.003","article-title":"A novel image template matching based on particle filtering optimization","volume":"31","author":"Li","year":"2010","journal-title":"Pattern Recognit. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"T\u00fcrkan, M., and Guillemot, C. (2010, January 26\u201329). Image prediction: Template matching vs. sparse approximation. Proceedings of the 17th International Conference on Image Processing, Hong Kong, China.","DOI":"10.1109\/ICIP.2010.5652548"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Lin, Y., and Chunbo, X. (2011, January 16\u201317). Template matching algorithm based on edge detection. Proceedings of the International Symposium on Computer Science and Society, Kota Kinabalu, Malaysia.","DOI":"10.1109\/ISCCS.2011.9"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"935","DOI":"10.3724\/SP.J.1187.2010.00935","article-title":"Detection and tracking control for air moving target based on dynamic template matching","volume":"24","author":"Lu","year":"2010","journal-title":"J. Electron. Meas. Instrum."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"14106","DOI":"10.3390\/s140814106","article-title":"Relevance\u2013based template matching for tracking targets in FLIR imagery","volume":"14","author":"Paravati","year":"2014","journal-title":"Sensors"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"6360","DOI":"10.3390\/s150306360","article-title":"A model\u2013based 3D template matching technique for pose acquisition of an uncooperative space object","volume":"15","author":"Opromolla","year":"2015","journal-title":"Sensors"},{"key":"ref_56","unstructured":"Welch, G., and Bishop, G. (2001, January 12\u201317). An introduction to the Kalman filter. Proceedings of the Special Interest Group on GRAPHics and Interactive Techniques (SIGGRAPH), Los Angeles, CA, USA."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1016\/j.procs.2015.09.027","article-title":"Survey on image segmentation techniques","volume":"65","author":"Zaitoun","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_58","first-page":"104","article-title":"Image segmentation based on watershed and edge detection techniques","volume":"3","author":"Salman","year":"2006","journal-title":"Int. Arab. J. Inf. Technol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"93","DOI":"10.5566\/ias.v28.p93-102","article-title":"Image segmentation: A watershed transformation algorithm","volume":"28","author":"Belaid","year":"2009","journal-title":"Image Anal. Stereol."},{"key":"ref_60","first-page":"1","article-title":"An improved watershed image segmentation technique using MATLAB","volume":"3","author":"Bala","year":"2012","journal-title":"Int. J. Sci. Eng. Res."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2013\/120798","article-title":"A novel model of image segmentation based on watershed algorithm","volume":"2013","author":"Yahya","year":"2013","journal-title":"Adv. Multimed."},{"key":"ref_62","first-page":"120","article-title":"A comparative study of thresholding algorithms on breast area and fibroglandular tissue","volume":"6","author":"Uyun","year":"2015","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_63","unstructured":"Gonzalez, R.C., and Woods, R.E. (2010). Digital Image Processing, Pearson Education Inc.. [3rd ed.]."},{"key":"ref_64","unstructured":"(2017, May 19). ARM Processors. Available online: https:\/\/www.arm.com\/products\/processors."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Lee, H., Jung, S., and Shim, D.H. (2016, January 7\u201310). Vision\u2013based UAV landing on the moving vehicle. Proceedings of the International Conference on Unmanned Aircraft System, Arlington, MA, USA.","DOI":"10.1109\/ICUAS.2016.7502574"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/s16091406","article-title":"Onboard robust visual tracking for UAVs using a reliable global\u2013local object model","volume":"16","author":"Fu","year":"2016","journal-title":"Sensors"},{"key":"ref_67","unstructured":"(2017, April 27). Intel\u00ae NUC Kit NUC5i7RYH. Available online: https:\/\/ark.intel.com\/products\/87570\/Intel\u2013NUC\u2013Kit\u2013NUC5i7RYH."},{"key":"ref_68","unstructured":"(2017, May 19). OpenCV 3.1. Available online: http:\/\/opencv.org\/opencv\u20133\u20131.html."},{"key":"ref_69","unstructured":"(2017, May 19). Microsoft Visual Studio. Available online: https:\/\/www.visualstudio.com\/."},{"key":"ref_70","unstructured":"(2017, May 19). CMake. Available online: https:\/\/cmake.org\/."},{"key":"ref_71","unstructured":"(2017, May 19). Stanford Drone Dataset. Available online: http:\/\/cvgl.stanford.edu\/projects\/uav_data\/."},{"key":"ref_72","unstructured":"(2017, May 19). Mini\u2013Drone Video Dataset. Available online: http:\/\/mmspg.epfl.ch\/mini\u2013drone."},{"key":"ref_73","unstructured":"(2017, May 19). SenseFly Dataset. Available online: https:\/\/www.sensefly.com\/drones\/example\u2013datasets.html."},{"key":"ref_74","unstructured":"(2017, June 16). Dongguk Drone Camera Database (DDroneC\u2013DB1). Available online: http:\/\/dm.dgu.edu\/link.html."},{"key":"ref_75","unstructured":"(2017, August 13). Chessboard Pattern. Available online: http:\/\/docs.opencv.org\/3.1.0\/pattern.png."},{"key":"ref_76","unstructured":"(2017, August 13). Camera Calibration and 3D Reconstruction. Available online: http:\/\/docs.opencv.org\/2.4\/modules\/calib3d\/doc\/camera_calibration_and_3d_reconstruction.html."},{"key":"ref_77","unstructured":"(2017, August 13). Detection of ArUco Markers. Available online: http:\/\/docs.opencv.org\/trunk\/d5\/dae\/tutorial_aruco_detection.html."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"2280","DOI":"10.1016\/j.patcog.2014.01.005","article-title":"Automatic generation and detection of highly reliable fiducial markers under occlusion","volume":"47","year":"2014","journal-title":"Pattern Recognit."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/9\/1987\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:43:39Z","timestamp":1760208219000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/9\/1987"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,30]]},"references-count":78,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["s17091987"],"URL":"https:\/\/doi.org\/10.3390\/s17091987","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,30]]}}}