Literatura académica sobre el tema "Image-based positioning"
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Artículos de revistas sobre el tema "Image-based positioning"
Zhang, Wei Guo y Chuan You Zhang. "Fast Image Positioning Based on Mark". Advanced Materials Research 756-759 (septiembre de 2013): 4090–94. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.4090.
Texto completoKlein, Kristina, Franziska Völckner, Hernán A. Bruno, Henrik Sattler y Pascal Bruno. "Brand Positioning Based on Brand Image–Country Image Fit". Marketing Science 38, n.º 3 (mayo de 2019): 516–38. http://dx.doi.org/10.1287/mksc.2019.1151.
Texto completoLi, X. y J. Wang. "EVALUATING PHOTOGRAMMETRIC APPROACH OF IMAGE-BASED POSITIONING". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences I-2 (13 de julio de 2012): 183–88. http://dx.doi.org/10.5194/isprsannals-i-2-183-2012.
Texto completoLiu, Xun, He Huang y Bo Hu. "Indoor Visual Positioning Method Based on Image Features". Sensors and Materials 34, n.º 1 (31 de enero de 2022): 337. http://dx.doi.org/10.18494/sam3562.
Texto completoFioravanti, Duccio, Benedetto Allotta y Andrea Rindi. "Image based visual servoing for robot positioning tasks". Meccanica 43, n.º 3 (29 de noviembre de 2007): 291–305. http://dx.doi.org/10.1007/s11012-007-9095-1.
Texto completoLin, Jian Hua, Gang Fu y Xue Lu Yao. "An Accurate Positioning Method of Image Target Based on Sub-Pixel". Applied Mechanics and Materials 644-650 (septiembre de 2014): 1274–77. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1274.
Texto completoZhang, Huiqing y Yueqing Li. "LightGBM Indoor Positioning Method Based on Merged Wi-Fi and Image Fingerprints". Sensors 21, n.º 11 (25 de mayo de 2021): 3662. http://dx.doi.org/10.3390/s21113662.
Texto completoSun, Senzhen, Guangyun Li, Yangjun Gao y Li Wang. "Robust Dynamic Indoor Visible Light Positioning Method Based on CMOS Image Sensor". Photogrammetric Engineering & Remote Sensing 88, n.º 5 (1 de mayo de 2022): 333–42. http://dx.doi.org/10.14358/pers.21-00077r3.
Texto completoBai, Nan, Guangzhu Chen, Rui Hou y Feng Ying. "A novel WiFi signal and RGB image fusion positioning method for manufacturing workshop". Journal of Intelligent & Fuzzy Systems 39, n.º 3 (7 de octubre de 2020): 3229–40. http://dx.doi.org/10.3233/jifs-191647.
Texto completoQiu, Yijin, Xingjie Chen y Zhaomin Lv. "Rail Fastener Positioning Based on Double Template Matching". Complexity 2020 (5 de octubre de 2020): 1–10. http://dx.doi.org/10.1155/2020/8316969.
Texto completoTesis sobre el tema "Image-based positioning"
Aeddula, Omsri Kumar. "Automatic Image Based Positioning System". Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15224.
Texto completoLavieri, Rodrigo Sauri. "Image-based wave feed-forward for dynamic positioning system". Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12122016-090140/.
Texto completoOs sistemas atuais de Posicionamento Dinâmico (DP) empregam técnicas de controle baseadas na realimentação da posição e do aproamento, associadas à compensação antecipada das cargas de vento (wind feed-forward) para manter a posição da embarcação. Esta tecnologia melhora a experiência do DP, pois antecipa a ação do vento. Entretanto, não há tecnologia consolidada para a pré-compensação de forças ondas (wave feed-forward) e o maior desafio reside na medição desses agentes ambientais. A presente tese tem como objetivo preencher essa lacuna tecnológica propondo uma abordagem alternativa para a medição das ondas próxima ao casco. Métodos de medição baseados em imagem são não invasivos e produzem descrições espaciais e temporais da superfície analisada, tornando-os particularmente adequados à medição de superfícies líquidas. Entretanto, os métodos comumente empregados, principalmente aqueles baseados em imagens estéreo, são incapazes de medir ondas produzidas em ambiente de laboratório, pois, nestas condições, a superfície da água é lisa, apresenta transparência e comporta-se como um espelho. Por outro lado, métodos baseados na intensidade de luz são capazes de lidar com tais características, se aplicados em condições adequadas e quando empregam modelos apropriados. Neste trabalho, um modelo de reetância amplamente conhecido é empregado para extrair os parâmetros principais de ondas regulares produzidas em um tanque de provas offshore. Inicialmente, propõe-se um arranjo experimental que permita a aplicação do modelo de refetância construído, mesmo sob as condições de iluminação naturais do laboratório. Posteriormente, um segundo conjunto de experimentos com um modelo de embarcação DP é proposto, no qual se aplica o método baseado em imagem, testado anteriormente, como sistema de pré-compensação de forças de onda. Três métodos de controle são avaliados, quais sejam: PID (Proporcional-Integral-Derivativo), PD (Proporcional-Derivativo) e o PD-WFF (PD associado ao wave feed-forward). Os resultados demonstram que a presença pré-conpensação de forças de onda reduz o erro em regime do controlador PD. Estes são os primeiros passos em direção da incorporação da pré-compensação de forças de onda nos sistemas DP reais e diversos aspectos técnicos ainda estão pendentes. Entretanto, os resultados promissores e discussões acerca dos futuros passos da pesquisa definem a contribuição do presente trabalho no campo do Posicionamento Dinâmico.
Audu, Abdulkadir Iyyaka. "Camera positioning for 3D panoramic image rendering". Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/10444.
Texto completoParra, Nestor Andres. "Rigid and Non-rigid Point-based Medical Image Registration". FIU Digital Commons, 2009. http://digitalcommons.fiu.edu/etd/127.
Texto completoMANZO, MARIO. "ATTRIBUTED RELATIONAL SIFT-BASED REGIONS GRAPH (ARSRG):DESCRIPTION, MATCHING AND APPLICATIONS". Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/233320.
Texto completoDI, PIETRA VINCENZO. "Seamless Positioning and Navigation in Urban Environment". Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2732878.
Texto completoAgmell, Simon y Marcus Dekker. "IR-Based Indoor Localisation and Positioning System". Thesis, Linköpings universitet, Fysik och elektroteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158175.
Texto completoConradie, Jean-Pierre. "Fluoroscopy based needle-positioning system for percutaneous nephrolithotomy procedures". Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/1768.
Texto completoA fluoroscopy-guided needle-positioning system is designed and tested as a first prototype for aiding urologists in gaining fast, accurate and repeatable kidney calyx access during a PCNL procedure while also reducing radiation exposure of the people involved. Image guidance is realized by modelling the fluoroscopic system as an adapted pinhole camera model and utilizing stereo vision principles on a stereo image pair. Calibration, distortion correction and image processing algorithms are implemented on images of a designed calibration object. Thereafter the resulting variables are used in the targeting of the calyx with the aid of a graphical user interface. The required relative translation and rotation of the needle from its current position to the target is calculated and the system is adjusted accordingly. Using digital cameras, needle placement accuracies of 2.5 mm is achieved within the calibrated volume in a simulated environment. Similar results are achieved in the surgery room environment using the fluoroscopic system. Successful needle access in two porcine kidney calyxes concluded the testing
Wei, Xiao y 魏驍. "Image-Based Ego-Positioning". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/29766583006145234369.
Texto completo國立臺灣大學
資訊網路與多媒體研究所
103
This thesis proposes an image-based ego-positioning framework to achieve sub-meter accuracy, with compact reference database compared to previous work, which can be used for the positioning of Internet connected devices. Consumer GPS devices nowadays obtain accuracy around several meters, which could be worse or even unable to work depending on the connection with GPS satellites. Current researches on image-based positioning utilize images and the reference database in different ways, however their accuracy, time consumption or database size have set limitations of their application. Experiments on different scenes in this work demonstrate that the method we proposed effectively reduce the size of reference database while main- taining a sub-meter accuracy for positioning. With evaluated performance, influencing factors are investigated, open problems are discussed for further improvements and applications.
LI, YU-CHENG y 李昱誠. "Indoor Precise Positioning System Based on Beacon Micro-Positioning and Image Recognition". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/c42bsa.
Texto completo國立宜蘭大學
資訊工程學系碩士班
106
Global Positioning System (GPS) can provide instantly outdoor position, but GPS are affected by shelter or buildings when positioned in indoors. Signal error of GPS will become very large. Therefore, when the indoor environment cannot be located using GPS. Other indoor positioning technologies are needed to solve the indoor positioning problem. This study explores an indoor positioning method that can be easily used by users and managers. But each of the indoor positioning methods must causes some errors, this study will explore how to achieve the goal of precise positioning by combining other techniques to reduce the error value in the original error. This paper mainly uses Bluetooth Low Energy as the main architecture. On the device, Bluetooth Low Energy's technology provides an indoor positioning method that is compatible with most smart phones and tablets on the market, as well as low power consumption, low cost of construction and easy deployment. Using Beacon and Fingerprinting to detect indoor positioning, and then using Fast corner feature extraction and Hog feature comparison, finally, the angle difference and the scaling ratio are calculated to find the angle and displacement distance. According to the above that getting the actual location of the user and achieving the goal of accurate indoor position. According to the experimental results of this paper, after the user uses Beacon to build the environment, without additional equipment, just a smartphone or tablet can being used to perform the indoor position. That not only reducing the burden of cost but also through image processing and feature point matching to increase Beacon indoor positioning accuracy. For the problem of GPS indoor positioning error, it will be solved more efficiently.
Libros sobre el tema "Image-based positioning"
Geological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoGeological Survey (U.S.), ed. GPS and GIS-based data collection and image mapping in the Antarctic Peninsula. [Reston, VA]: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.
Buscar texto completoOctavia, Camps y United States. National Aeronautics and Space Administration., eds. Detection of obstacles in monocular image sequences: Final technical report for NASA co-operative research agreement number NCC 2-916, "A vision-based obstacle detection system for aircraft navigation," period of grant--August 1, 1995 to July 31, 1997. [Washington, DC: National Aeronautics and Space Administration, 1997.
Buscar texto completoNoureldin, Aboelmagd. Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
Buscar texto completoCapítulos de libros sobre el tema "Image-based positioning"
Haga, Akihiro. "X-Ray Image-Based Patient Positioning". En Image-Based Computer-Assisted Radiation Therapy, 199–235. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2945-5_9.
Texto completoSoufi, Mazen y Hidetaka Arimura. "Surface-Imaging-Based Patient Positioning in Radiation Therapy". En Image-Based Computer-Assisted Radiation Therapy, 237–70. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2945-5_10.
Texto completoLiang, Jason Zhi, Nicholas Corso, Eric Turner y Avideh Zakhor. "Image-Based Positioning of Mobile Devices in Indoor Environments". En Multimodal Location Estimation of Videos and Images, 85–99. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09861-6_5.
Texto completoYun, JaeMu, EunTae Lyu y JangMyung Lee. "Image-Based Absolute Positioning System for Mobile Robot Navigation". En Lecture Notes in Computer Science, 261–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11815921_28.
Texto completoMa, Luxi, Qinmu Wu, Yu Zhan, Bohai Liu y Xianpeng Wang. "Traffic Sign Detection Based on Improved YOLOv3 in Foggy Environment". En Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 685–95. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_70.
Texto completoGuo, Xiaomeng, Danyang Qin y Yan Yang. "Indoor Visual Positioning Based on Image Retrieval in Dense Connected Convolutional Network". En Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 70–79. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69066-3_7.
Texto completoWang, Zhonghong, Guoqiang Wang y Guoying Zhang. "Research on Image Retrieval Based on Wavelet Denoising in Visual Indoor Positioning Algorithm". En Lecture Notes in Electrical Engineering, 1385–91. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9409-6_166.
Texto completoHatem, I., M. Jamal, Y. Murhij y Z. Ali. "Low-Cost Quadcopter Indoor Positioning System Based on Image Processing and Neural Networks". En Mechanism, Machine, Robotics and Mechatronics Sciences, 243–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89911-4_18.
Texto completoWei, Chunyang, Hao Xia y Yanyou Qiao. "An Improved Image Positioning Method Based on Local Changed Plane Eliminated by Homography". En Lecture Notes in Computer Science, 3–14. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34110-7_1.
Texto completoDai, Honghui, Chenge Geng y Taotao Lu. "Research on Assisted Train Positioning Method of Urban Rail Based on Image Matching". En Lecture Notes in Electrical Engineering, 1124–36. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2259-6_100.
Texto completoActas de conferencias sobre el tema "Image-based positioning"
Kawaji, Hisato, Koki Hatada, Toshihiko Yamasaki y Kiyoharu Aizawa. "Image-based indoor positioning system". En the 1st ACM international workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878039.1878041.
Texto completoTian, Shengjun. "A Positioning Method based on Image". En 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/mecs-17.2017.134.
Texto completoLi, Yunzhi, Rajeswari Hita Kambhamettu, Yidan Hu y Rui Zhang. "ImPos: An Image-Based Indoor Positioning System". En 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2022. http://dx.doi.org/10.1109/ccnc49033.2022.9700699.
Texto completoRenshaw, C. Kyle, Jennifer Hewitt, Robert Grimming y Ronald G. Driggers. "Sensor Optimization for Image-Based Geolocation". En Computational Optical Sensing and Imaging. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cosi.2022.jf2d.6.
Texto completoLopez-Antequera, Manuel, Nicolai Petkov y Javier Gonzalez-Jimenez. "Image-based localization using Gaussian processes". En 2016 7th International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2016. http://dx.doi.org/10.1109/ipin.2016.7743697.
Texto completoJun-Ren Ding, Jiun-Yu Chen, Fu-Chun Yang y Jar-Ferr Yang. "Image-based auto-positioning brush for LCD displays". En ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4518075.
Texto completoBorstell, Hagen, Saira Pathan, Liu Cao, Klaus Richter y Mykhaylo Nykolaychuk. "Vehicle positioning system based on passive planar image markers". En 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2013. http://dx.doi.org/10.1109/ipin.2013.6817875.
Texto completoSchwiegelshohn, F., T. Nick y J. Gotze. "Localization based on fusion of RFID and stereo image data". En 2013 10th Workshop on Positioning, Navigation and Communication (WPNC). IEEE, 2013. http://dx.doi.org/10.1109/wpnc.2013.6533297.
Texto completoChen, Hong Ming, Ting En Lee, Juhng Perng Su y Chyun Luen Lin. "Realization of an Image-Based XXY Positioning Platform Control". En 2014 International Symposium on Computer, Consumer and Control (IS3C). IEEE, 2014. http://dx.doi.org/10.1109/is3c.2014.308.
Texto completoMaruyama, Toshinori y Hideki Yamamoto. "CT image based training tool for positioning in radiography". En 2011 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2011. http://dx.doi.org/10.1109/ist.2011.5962172.
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