Qadri, M.T., Asif, M.: Automatic number plate recognition system for vehicle identification using optical character recognition. In: 2009 International Conference on Education Technology and Computer, pp. 335–338. IEEE (2009)
Google Scholar
He, L., Chao, Y., Suzuki, K., Wu, K.: Fast connected-component labeling. Pattern Recognit 42(9), 1977–1987 (2009)
CrossRef
Google Scholar
Nguyen, H., Maclagan, S.J., Nguyen, T.D., Nguyen, T., Flemons, P., Andrews, K., Ritchie, E.G., Phung, D.: Animal recognition and identification with deep convolutional neural networks for automated wildlife monitoring. In: 2017 IEEE international conference on data science and advanced Analytics (DSAA), pp. 40–49. IEEE (2017)
Google Scholar
Ray, S., Das, S., Sen, A.: An intelligent vision system for monitoring security and surveillance of atm. In: 2015 Annual IEEE India Conference (INDICON), pp. 1–5. IEEE (2015)
Google Scholar
Sutoyo, R., Harefa, J., Chowanda, A.: Unlock screen application design using face expression on android smartphone. In: MATEC Web of Conferences. vol. 54, p. 05001, EDP Sciences (2016)
Google Scholar
Cuevas, E., Díaz, M., Manzanares, M., Zaldivar, D., Perez-Cisneros, M.: An improved computer vision method for white blood cells detection. Computational and Mathematical Methods in Medicine (2013)
Google Scholar
Lee, H., Chen, Y.P.P.: Image based computer aided diagnosis system for cancer detection. Expert Syst Appl 42(12), 5356–5365 (2015)
CrossRef
Google Scholar
Al-Kaff, A., Moreno, F.M., de la Escalera, A., Armingol, J.M.: Intelligent vehicle for search, rescue and transportation purposes. In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 110–115. IEEE (2017)
Google Scholar
Perez-Grau, F., Ragel, R., Caballero, F., Viguria, A., Ollero, A.: Semi-autonomous teleoperation of uavs in search and rescue scenarios. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1066–1074. IEEE (2017)
Google Scholar
Shirwalkar, S., Singh, A., Sharma, K., Singh, N.: Telemanipulation of an industrial robotic arm using gesture recognition with kinect. In: 2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE), pp. 1–6. IEEE (2013)
Google Scholar
Rashid, M., Han, X.: Gesture control of zigbee connected smart home internet of things. In: 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV), pp. 667–670. IEEE (2016)
Google Scholar
Hsiao, H.S., Chen, J.C.: Using a gesture interactive game-based learning approach to improve preschool children’s learning performance and motor skills. Comput Educat 95, 151–162 (2016)
CrossRef
Google Scholar
Rahman, A.M., Hossain, M.A., Parra, J., El Saddik, A.: Motion-path based gesture interaction with smart home services. In: Proceedings of the 17th ACM international conference on Multimedia, pp. 761–764 (2009)
Google Scholar
Hussain, S., Schaffner, S., Moseychuck, D.: Applications of wireless sensor networks and rfid in a smart home environment. In: 2009 Seventh Annual Communication Networks and Services Research Conference, pp. 153–157. IEEE (2009)
Google Scholar
Muñoz-Salinas, R., Medina-Carnicer, R., Madrid-Cuevas, F.J., Carmona-Poyato, A.: Depth silhouettes for gesture recognition. Pattern Recognit Lett 29(3), 319–329 (2008)
CrossRef
Google Scholar
Pal, M.: Random forest classifier for remote sensing classification. Int J Remote Sensing 26(1), 217–222 (2005)
CrossRef
Google Scholar
Rautaray, S.S.: Real time hand gesture recognition system for dynamic applications. Int J UbiComp (IJU) 3(1) (2012)
Google Scholar
Vivek Veeriah, J., Swaminathan, P.: Robust hand gesture recognition algorithm for simple mouse control. Int J Comput Commun Eng 2(2), 219–221 (2013)
CrossRef
Google Scholar
Galin, R., Meshcheryakov, R.: Review on human–robot interaction during collaboration in a shared workspace. In: International Conference on Interactive Collaborative Robotics, pp. 63–74. Springer (2019)
Google Scholar
Malov, D., Edemskii, A., Saveliev, A.: Architecture of proactive localization service for cyber-physical system’s users. In: International Conference on Interactive Collaborative Robotics, pp. 10–18. Springer (2019)
Google Scholar
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). Comput Vision Image Understanding 110(3), 346–359 (2008)
CrossRef
Google Scholar
Goel, A., Saxena, S.C., Bhanot, S.: Modified functional link artificial neural network. Int J Electri Comput Eng 1(1), 22–30 (2006)
Google Scholar
Tang, G., Webb, P.: The design and evaluation of an ergonomic contactless gesture control system for industrial robots. J Robotics (2018)
Google Scholar
Chen, S., Ma, H., Yang, C., Fu, M.: Hand gesture based robot control system using leap motion. In: International Conference on Intelligent Robotics and Applications, pp. 581–591. Springer (2015)
Google Scholar
Mikadlicki, K., Pajor, M.: Real-time gesture control of a CNC machine tool with the use Microsoft Kinect sensor. Int J Sci Eng Res 6(9), 538–543 (2015)
Google Scholar
Grif, H.S., Farcas, C.C.: Mouse cursor control system based on hand gesture. Procedia Technol 22, 657–661 (2016)
CrossRef
Google Scholar
Song, S., Yan, D., Xie, Y.: Design of control system based on hand gesture recognition. In: 2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC), pp. 1–4. IEEE (2018)
Google Scholar
Phyo, A.S., Fukuda, H., Lam, A., Kobayashi, Y., Kuno, Y.: A human-robot interaction system based on calling hand gestures. In: International Conference on Intelligent Computing, pp. 43–52. Springer (2019)
Google Scholar
Gao, X., Shi, L., Wang, Q.: The design of robotic wheelchair control system based on hand gesture control for the disabled. In: 2017 International Conference on Robotics and Automation Sciences (ICRAS), pp. 30–34. IEEE (2017)
Google Scholar
Zhang, B., Yang, M., Yuan, W., Wang, C., Wang, B.: A novel system for guiding unmanned vehicles based on human gesture recognition. In: 2020 IEEE International Conference on Real-time Computing and Robotics (RCAR), pp. 345–350. IEEE (2020)
Google Scholar
Zhang, Z.: Microsoft Kinect sensor and its effect. IEEE Multimedia 19(2), 4–10 (2012)
CrossRef
Google Scholar
Han, J., Shao, L., Xu, D., Shotton, J.: Enhanced computer vision with Microsoft Kinect sensor: a review. IEEE Transa Cybernet 43(5), 1318–1334 (2013)
CrossRef
Google Scholar
Safin, R., Lavrenov, R., Tsoy, T., Svinin, M., Magid, E.: Real-time video server implementation for a mobile robot. In: 2018 11th International Conference on Developments in eSystems Engineering (DeSE), pp. 180–185. IEEE (2018)
Google Scholar
Magid, E., Lavrenov, R., Khasianov, A.: Modified spline-based path planning for autonomous ground vehicle. In: ICINCO (2), pp. 132–141 (2017)
Google Scholar
Lavrenov, R., Zakiev, A.: Tool for 3d gazebo map construction from arbitrary images and laser scans. In: 2017 10th International Conference on Developments in eSystems Engineering (DeSE), pp. 256–261. IEEE (2017)
Google Scholar
Imameev, D., Shabalina, K., Sagitov, A., Su, K.L., Magid, E.: Modelling Autonomous Parallel Parking Procedure for Car-Like Robot Avrora Unior in Gazebo Simulator, pp. 428–431 (2020)
Google Scholar
Safin, R., Garipova, E., Lavrenov, R., Li, H., Svinin, M., Magid, E.: Hardware and software video encoding comparison. In: 2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), pp. 924–929. IEEE (2020)
Google Scholar
Imameev, D., Zakiev, A., Tsoy, T., Bai, Y., Svinin, M., Magid, E.: Lidar-based parking spot search algorithm. In: Thirteenth International Conference on Machine Vision. vol. 11605, p. 1160502. International Society for Optics and Photonics (2021)
Google Scholar
Shabalina, K., Sagitov, A., Su, K.L., Hsia, K.H., Magid, E.: Avrora unior car-like robot in gazebo environment. In: International Conference on Artificial Life and Robotics, pp. 116–119 (2019)
Google Scholar
Cao, Z., Hidalgo, G., Simon, T., Wei, S.E., Sheikh, Y.: Openpose: realtime multi-person 2d pose estimation using part affinity fields. IEEE Trans pattern Anal Mach Intell 43(1), 172–186 (2019)
CrossRef
Google Scholar
Carney, M., Webster, B., Alvarado, I., Phillips, K., Howell, N., Griffith, J., Jongejan, J., Pitaru, A., Chen, A.: Teachable machine: Approachable web-based tool for exploring machine learning classification. In: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–8 (2020)
Google Scholar