{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T15:30:59Z","timestamp":1778599859221,"version":"3.51.4"},"reference-count":92,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,18]],"date-time":"2015-09-18T00:00:00Z","timestamp":1442534400000},"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>Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032 \u00d7 778 resolution) and 150 ms outdoors (1280 \u00d7 720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms.<\/jats:p>","DOI":"10.3390\/s150923805","type":"journal-article","created":{"date-parts":[[2015,9,21]],"date-time":"2015-09-21T02:25:40Z","timestamp":1442802340000},"page":"23805-23846","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":110,"title":["Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles"],"prefix":"10.3390","volume":"15","author":[{"given":"Fatih","family":"G\u00f6k\u00e7e","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University, \u00dcniversiteler Mahallesi, Dumlup\u0131nar Bulvar\u0131 No. 1, 06800 \u00c7ankaya Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"G\u00f6kt\u00fcrk","family":"\u00dc\u00e7oluk","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University, \u00dcniversiteler Mahallesi, Dumlup\u0131nar Bulvar\u0131 No. 1, 06800 \u00c7ankaya Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erol","family":"\u015eahin","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University, \u00dcniversiteler Mahallesi, Dumlup\u0131nar Bulvar\u0131 No. 1, 06800 \u00c7ankaya Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sinan","family":"Kalkan","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University, \u00dcniversiteler Mahallesi, Dumlup\u0131nar Bulvar\u0131 No. 1, 06800 \u00c7ankaya Ankara, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1139\/cjfr-2014-0347","article-title":"A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques","volume":"45","author":"Yuan","year":"2015","journal-title":"Can. J. For. Res."},{"key":"ref_3","unstructured":"Ackerman, E. When Drone Delivery Makes Sense. Available online: http:\/\/spectrum.ieee.org\/automaton\/robotics\/aerial-robots\/when-drone-delivery-makes-sense."},{"key":"ref_4","unstructured":"Holmes, K. Man Detained Outside White House for Trying to Fly Drone. Available online: http:\/\/edition.cnn.com\/2015\/05\/14\/politics\/white-house-drone-arrest\/."},{"key":"ref_5","unstructured":"Martinez, M., Vercammen, P., and Brumfield, B. Above spectacular wildfire on freeway rises new scourge: Drones. Available online: http:\/\/edition.cnn.com\/2015\/07\/18\/us\/california-freeway-fire\/."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1016\/j.cviu.2013.04.005","article-title":"50 Years of object recognition: Directions forward","volume":"117","author":"Andreopoulos","year":"2013","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1006\/cviu.2000.0889","article-title":"A survey of free-form object representation and recognition techniques","volume":"81","author":"Campbell","year":"2001","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_8","first-page":"1150","article-title":"Object recognition from local scale-invariant features","volume":"2","author":"Lowe","year":"1999","journal-title":"Int. Conf. Comput. Vis."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1109\/34.993558","article-title":"Shape matching and object recognition using shape contexts","volume":"24","author":"Belongie","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_10","first-page":"511","article-title":"Rapid object detection using a boosted cascade of simple features","volume":"1","author":"Viola","year":"2001","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"ref_11","first-page":"886","article-title":"Histograms of oriented gradients for human detection","volume":"1","author":"Dalal","year":"2005","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1109\/TPAMI.2007.56","article-title":"Robust object recognition with cortex-like mechanisms","volume":"29","author":"Serre","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1757","DOI":"10.1016\/j.patcog.2004.03.009","article-title":"Learning multi-label scene classification","volume":"37","author":"Boutell","year":"2004","journal-title":"Pattern Recog."},{"key":"ref_14","first-page":"430","article-title":"Machine Learning for High-Speed Corner Detection","volume":"3951","author":"Rosten","year":"2006","journal-title":"Eur. Conf. Comput. Vis."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/S0262-8856(97)00056-5","article-title":"Fast corner detection","volume":"16","author":"Trajkovic","year":"1998","journal-title":"Image Vis. Comput."},{"key":"ref_16","unstructured":"Harris, C., and Stephens, M. (September, January 31). A Combined Corner and Edge Detector. Proceedings of the 4th Alvey Vision Conference, Manchester, UK."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Matas, J., Chum, O., Urban, M., and Pajdla, T. (2002, January 2\u20135). Robust Wide Baseline Stereo from Maximally Stable Extremal Regions. Proceedings of the British Machine Vision Conference, Cardiff, UK.","DOI":"10.5244\/C.16.36"},{"key":"ref_18","unstructured":"Shi, J., and Tomasi, C. (1994, January 21\u201323). Good features to track. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1561\/0600000017","article-title":"Local invariant feature detectors: A survey","volume":"3","author":"Tuytelaars","year":"2008","journal-title":"Found. Trends Comput. Graph. Vis."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded-Up Robust Features (SURF)","volume":"110","author":"Bay","year":"2008","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive Image Features from Scale-Invariant Keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_22","first-page":"778","article-title":"BRIEF: Binary Robust Independent Elementary Features","volume":"6314","author":"Calonder","year":"2010","journal-title":"Eur. Conf. Comput. Vis."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., and Bradski, G.R. (2011). ORB: An efficient alternative to SIFT or SURF. Int. Conf. Comput. Vis., 2564\u20132571.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Leutenegger, S., Chli, M., and Siegwart, R.Y. (2011, January 6\u201313). BRISK: Binary Robust Invariant Scalable Keypoints. Proceedings of the IEEE International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126542"},{"key":"ref_25","unstructured":"Vandergheynst, P., Ortiz, R., and Alahi, A. (2012, January 16\u201321). FREAK: Fast Retina Keypoint. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA."},{"key":"ref_26","first-page":"1800","article-title":"Object categorization by learned universal visual dictionary","volume":"2","author":"Winn","year":"2005","journal-title":"Int. Conf. Comput. Vis."},{"key":"ref_27","unstructured":"Murphy, K., Torralba, A., Eaton, D., and Freeman, W. (2006). Toward Category-Level Object Recognition, Springer."},{"key":"ref_28","unstructured":"Csurka, G., Dance, C.R., Fan, L., Willamowski, J., and Bray, C. (2001, January 10\u201316). Visual categorization with bags of keypoints. Proceedings of the Workshop on Statistical Learning in Computer Vision, ECCV, Prague, Czech Republic."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_30","unstructured":"Pereira, F., Burges, C., Bottou, L., and Weinberger, K. (2012). Advances in Neural Information Processing Systems (NIPS) 25, Curran Associates, Inc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ref_32","unstructured":"Dietterich, T.G. (2000). Multiple Classifier Systems, Springer."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1109\/34.655647","article-title":"Neural network-based face detection","volume":"20","author":"Rowley","year":"1998","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","article-title":"Robust real-time face detection","volume":"57","author":"Viola","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_35","unstructured":"Freund, Y., and Schapire, R.E. (1995). Computational Learning Theory, Springer."},{"key":"ref_36","unstructured":"Liao, S., Zhu, X., Lei, Z., Zhang, L., and Li, S.Z. (2007). Advances in Biometrics, Springer."},{"key":"ref_37","first-page":"1491","article-title":"Fast human detection using a cascade of histograms of oriented gradients","volume":"2","author":"Zhu","year":"2006","journal-title":"IEEE Conf. Comput. Vis. Pattern Recog."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"7566","DOI":"10.3390\/s90907566","article-title":"Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors","volume":"9","author":"Heredia","year":"2009","journal-title":"Sensors"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"9408","DOI":"10.3390\/s140609408","article-title":"Multi-Agent Cooperative Target Search","volume":"14","author":"Hu","year":"2014","journal-title":"Sensors"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1090","DOI":"10.3390\/rs4041090","article-title":"A Real-Time Method to Detect and Track Moving Objects (DATMO) from Unmanned Aerial Vehicles (UAVs) Using a Single Camera","volume":"4","author":"Thomas","year":"2012","journal-title":"Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/s10514-012-9292-1","article-title":"Optimal Surveillance Coverage for Teams of Micro Aerial Vehicles in GPS-Denied Environments Using Onboard Vision","volume":"33","author":"Doitsidis","year":"2012","journal-title":"Auton. Robots"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Saska, M., Chudoba, J., Precil, L., Thomas, J., Loianno, G., Tresnak, A., Vonasek, V., and Kumar, V. (2014, January 27\u201330). Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance. Proceedings of the 2014 International Conference on Unmanned Aircraft Systems (ICUAS), Orlando, FL, USA.","DOI":"10.1109\/ICUAS.2014.6842301"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"453","DOI":"10.3390\/s120100453","article-title":"Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera","volume":"12","author":"Rosnell","year":"2012","journal-title":"Sensors"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Shen, S., Mulgaonkar, Y., Michael, N., and Kumar, V. (2013, January 6\u201310). Vision-based State Estimation for Autonomous Rotorcraft MAVs in Complex Environments. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6630808"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Shen, S., Mulgaonkar, Y., Michael, N., and Kumar, V. (2013, January 24\u201328). Vision-Based State Estimation and Trajectory Control Towards Aggressive Flight with a Quadrotor. Proceedings of the Robotics: Science and Systems (RSS), Berlin, Germany.","DOI":"10.15607\/RSS.2013.IX.032"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Shen, S., Mulgaonkar, Y., Michael, N., and Kumar, V. (2014, January 15\u201318). Initialization-Free Monocular Visual-Inertial Estimation with Application to Autonomous MAVs. Proceedings of the International Symposium on Experimental Robotics, Marrakech, Morocco.","DOI":"10.1007\/978-3-319-23778-7_15"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Scaramuzza, D., Achtelik, M.C., Doitsidis, L., Fraundorfer, F., Kosmatopoulos, E.B., Martinelli, A., Achtelik, M.W., Chli, M., Chatzichristofis, S.A., and Kneip, L. (2014). Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-denied Environments. IEEE Robot. Autom. Mag., 21.","DOI":"10.1109\/MRA.2014.2322295"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Achtelik, M., Weiss, S., Chli, M., Dellaert, F., and Siegwart, R. (2011, January 25\u201330). Collaborative Stereo. Proceedings of the IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6048550"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1177\/0278364913509675","article-title":"Camera-IMU-based localization: Observability analysis and consistency improvement","volume":"33","author":"Hesch","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1007\/s10846-014-0041-x","article-title":"A Practical Multirobot Localization System","volume":"76","author":"Krajnik","year":"2014","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Faigl, J., Krajnik, T., Chudoba, J., Preucil, L., and Saska, M. (2013, January 6\u201310). Low-cost embedded system for relative localization in robotic swarms. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6630694"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Lin, F., Peng, K., Dong, X., Zhao, S., and Chen, B. (2014, January 18\u201320). Vision-based formation for UAVs. Proceedings of the IEEE International Conference on Control Automation (ICCA), Taichung, Taiwan.","DOI":"10.1109\/ICCA.2014.6871124"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhang, M., Lin, F., and Chen, B. (2014, January 10\u201312). Vision-based detection and pose estimation for formation of micro aerial vehicles. Proceedings of the International Conference on Automation Robotics Vision (ICARCV), Singapore, Singapore.","DOI":"10.1109\/ICARCV.2014.7064533"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1002\/rob.20359","article-title":"Airborne vision-based collision-detection system","volume":"28","author":"Lai","year":"2011","journal-title":"J. Field Robot."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1007\/978-3-540-79547-6_46","article-title":"Learning to Detect Aircraft at Low Resolutions","volume":"Volume 5008","author":"Gasteratos","year":"2008","journal-title":"Computer Vision Systems"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Dey, D., Geyer, C., Singh, S., and Digioia, M. (2009, January 14\u201316). Passive, long-range detection of Aircraft: Towards a field deployable Sense and Avoid System. Proceedings of the Field and Service Robotics, Cambridge, MA, USA.","DOI":"10.1007\/978-3-642-13408-1_11"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1177\/0278364911412807","article-title":"A cascaded method to detect aircraft in video imagery","volume":"30","author":"Dey","year":"2011","journal-title":"Int. J. Robot. Res."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"V\u00e1s\u00e1rhelyi, G., Vir\u00e1gh, C., Somorjai, G., Tarcai, N., Sz\u00f6r\u00e9nyi, T., Nepusz, T., and Vicsek, T. (2014, January 14\u201318). Outdoor flocking and formation flight with autonomous aerial robots. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6943105"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Brewer, E., Haentjens, G., Gavrilets, V., and McGraw, G. (2014, January 5\u20138). A low SWaP implementation of high integrity relative navigation for small UAS. Proceedings of the Position, Location and Navigation Symposium, Monterey, CA, USA.","DOI":"10.1109\/PLANS.2014.6851490"},{"key":"ref_60","unstructured":"Roberts, J. (2011). Enabling Collective Operation of Indoor Flying Robots. [Ph.D. Thesis, Ecole Polytechnique Federale de Lausanne (EPFL)]."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10514-012-9277-0","article-title":"3-D Relative Positioning Sensor for Indoor Flying Robots","volume":"33","author":"Roberts","year":"2012","journal-title":"Auton. Robots"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Stirling, T., Roberts, J., Zufferey, J., and Floreano, D. (2012, January 14\u201318). Indoor Navigation with a Swarm of Flying Robots. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), St. Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6224987"},{"key":"ref_63","unstructured":"Welsby, J., Melhuish, C., Lane, C., and Qy, B. (2001, January 6\u20139). Autonomous minimalist following in three dimensions: A study with small-scale dirigibles. Proceedings of the Towards Intelligent Mobile Robots, Coventry, UK."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"16484","DOI":"10.3390\/s150716484","article-title":"HyperCube: A Small Lensless Position Sensing Device for the Tracking of Flickering Infrared LEDs","volume":"15","author":"Raharijaona","year":"2015","journal-title":"Sensors"},{"key":"ref_65","unstructured":"Etter, W., Martin, P., and Mangharam, R. (2011, January 11\u201314). Cooperative Flight Guidance of Autonomous Unmanned Aerial Vehicles. Proceedings of the CPS Week Workshop on Networks of Cooperating Objects, Chicago, IL, USA."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Basiri, M., Schill, F., Floreano, D., and Lima, P. (2013, January 24\u201328). Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems. Proceedings of the Robotics: Science and Systems (RSS), Berlin, Germany.","DOI":"10.15607\/RSS.2013.IX.002"},{"key":"ref_67","unstructured":"Tijs, E., de Croon, G., Wind, J., Remes, B., de Wagter, C., de Bree, H.E., and Ruijsink, R. (2010, January 6\u20139). Hear-and-Avoid for Micro Air Vehicles. Proceedings of the International Micro Air Vehicle Conference and Competitions (IMAV), Braunschweig, Germany."},{"key":"ref_68","unstructured":"Nishitani, A., Nishida, Y., and Mizoguch, H. (November, January 30). Omnidirectional ultrasonic location sensor. Proceedings of the IEEE Conference on Sensors, Irvine, CA, USA."},{"key":"ref_69","unstructured":"Maxim, P.M., Hettiarachchi, S., Spears, W.M., Spears, D.F., Hamann, J., Kunkel, T., and Speiser, C. (2008, January 11\u201315). Trilateration localization for multi-robot teams. Proceedings of the Sixth International Conference on Informatics in Control, Automation and Robotics, Special Session on MultiAgent Robotic Systems (ICINCO), Funchal, Madeira, Portugal."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Rivard, F., Bisson, J., Michaud, F., and Letourneau, D. (2008, January 19\u201323). Ultrasonic relative positioning for multi-robot systems. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA.","DOI":"10.1109\/ROBOT.2008.4543228"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Moses, A., Rutherford, M., and Valavanis, K. (2011, January 28\u201330). Radar-based detection and identification for miniature air vehicles. Proceedings of the IEEE International Conference on Control Applications (CCA), Denver, CO, USA.","DOI":"10.1109\/CCA.2011.6044363"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1017\/S0263574713000659","article-title":"UAV-borne X-band radar for collision avoidance","volume":"32","author":"Moses","year":"2014","journal-title":"Robotica"},{"key":"ref_73","unstructured":"Lienhart, R., and Maydt, J. (2002, January 11\u201315). An extended set of Haar-like features for rapid object detection. Proceedings of the International Conference on Image, Rochester, NY, USA."},{"key":"ref_74","unstructured":"Papageorgiou, C.P., Oren, M., and Poggio, T. (1998, January 4\u20137). A general framework for object detection. Proceedings of the International Conference on Computer Vision, Bombay, India."},{"key":"ref_75","unstructured":"Ojala, T., Pietikainen, M., and Harwood, D. (1994, January 9\u201313). Performance evaluation of texture measures with classification based on Kullback discrimination of distributions. Proceedings of the 12th IAPR International Conference on Pattern Recognition, Jerusalem, Israel."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1162\/089976600300015565","article-title":"New support vector algorithms","volume":"12","author":"Smola","year":"2000","journal-title":"Neural Comput."},{"key":"ref_77","unstructured":"3DRobotics Arducopter: Full-Featured, Open-Source Multicopter UAV Controller. Available online: http:\/\/copter.ardupilot.com\/."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Gaschler, A. (2011). Real-Time Marker-Based Motion Tracking: Application to Kinematic Model Estimation of a Humanoid Robot. [Master\u2019s Thesis, Technische Universit\u00e4t M\u00fcnchen].","DOI":"10.1007\/978-3-642-23123-0_45"},{"key":"ref_79","unstructured":"Gaschler, A., Springer, M., Rickert, M., and Knoll, A. (June, January 31). Intuitive Robot Tasks with Augmented Reality and Virtual Obstacles. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1364\/JOSAA.5.001127","article-title":"Closed-Form Solution of Absolute Orientation using Orthonormal Matrices","volume":"5","author":"Horn","year":"1988","journal-title":"J. Opt. Soc. Am."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1109\/34.88573","article-title":"Least-squares estimation of transformation parameters between two point patterns","volume":"13","author":"Umeyama","year":"1991","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_82","unstructured":"Bradski, G. The OpenCV Library. Available online: http:\/\/www.drdobbs.com\/open-source\/the-opencv-library\/184404319?queryText=opencv."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Remagnino, P., Jones, G., Paragios, N., and Regazzoni, C. (2002). Video-Based Surveillance Systems, Springer.","DOI":"10.1007\/978-1-4615-0913-4"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1111\/j.1469-8137.1912.tb05611.x","article-title":"The distribution of the flora in the Alpine zone","volume":"11","author":"Jaccard","year":"1912","journal-title":"New Phytol."},{"key":"ref_85","unstructured":"Rekleitis, I.M. (1995). Visual Motion Estimation based on Motion Blur Interpretation. [Master\u2019s Thesis, School of Computer Science, McGill University]."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Soe, A.K., and Zhang, X. (2012, January 19\u201321). A simple PSF parameters estimation method for the de-blurring of linear motion blurred images using wiener filter in OpenCV. Proceedings of the International Conference on Systems and Informatics (ICSAI), Yantai, China.","DOI":"10.1109\/ICSAI.2012.6223408"},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Hulens, D., Verbeke, J., and Goedeme, T. (2015, January 11\u201314). How to Choose the Best Embedded Processing Platform for on-Board UAV Image Processing?. Proceedings of the 10th International Conference on Computer Vision Theory and Applications, Berlin, Germany.","DOI":"10.5220\/0005359403770386"},{"key":"ref_88","unstructured":"AscendingTechnologies AscTec Mastermind. Available online: http:\/\/www.asctec.de\/en\/asctec-mastermind\/."},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Leibe, B., Schindler, K., and van Gool, L. (2007, January 14\u201321). Coupled detection and trajectory estimation for multi-object tracking. Proceedings of the IEEE International Conference on Computer Vision (ICCV), Rio de Janeiro, Brazil.","DOI":"10.1109\/ICCV.2007.4408936"},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Huang, C., Wu, B., and Nevatia, R. Robust object tracking by hierarchical association of detection. 788\u2013801.","DOI":"10.1007\/978-3-540-88688-4_58"},{"key":"ref_91","unstructured":"Stalder, S., Grabner, H., and van Gool, L. (2010). European Conference on Computer Vision, Springer."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1109\/TPAMI.2011.155","article-title":"Pedestrian detection: An evaluation of the state of the art","volume":"34","author":"Dollar","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/9\/23805\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:49Z","timestamp":1760215729000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/9\/23805"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,18]]},"references-count":92,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["s150923805"],"URL":"https:\/\/doi.org\/10.3390\/s150923805","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,9,18]]}}}