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Relevant bibliographies by topics / Real-time Localization

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Academic literature on the topic 'Real-time Localization'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 April 2023

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Journal articles on the topic "Real-time Localization"

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Atiya, S., and G. D. Hager. "Real-time vision-based robot localization." IEEE Transactions on Robotics and Automation 9, no. 6 (1993): 785–800. http://dx.doi.org/10.1109/70.265922.

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B. C. Heidman and U. A. Rosa. "Real-Time Tree Localization in Orchards." Applied Engineering in Agriculture 24, no. 6 (2008): 707–16. http://dx.doi.org/10.13031/2013.25360.

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Singer, Robert H. "RNA localization: visualization in real-time." Current Biology 13, no. 17 (September 2003): R673—R675. http://dx.doi.org/10.1016/s0960-9822(03)00605-5.

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Xin You, Xin You, Daxin Tian Xin You, Chen Liu Daxin Tian, Xiaofeng Yu Chen Liu, and Liangliang Song Xiaofeng Yu. "Vehicles Positioning in Tunnel: A Real-Time Localization System Using DL-TDOA Technology." 網際網路技術學刊 22, no. 5 (September 2021): 965–76. http://dx.doi.org/10.53106/160792642021092205003.

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Oyama, D., Y. Adachi, M. Higuchi, J. Kawai, M. Miyamoto, K. Kobayashi, and G. Uehara. "Real-time Head Localization System for Magnetoencephalography." Journal of the Magnetics Society of Japan 36, no. 6 (2012): 345–51. http://dx.doi.org/10.3379/msjmag.1209r003.

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Bouvet, Denis, Michel Froumentin, and Gaëtan Garcia. "A real-time localization system for compactors." Automation in Construction 10, no. 4 (May 2001): 417–28. http://dx.doi.org/10.1016/s0926-5805(00)00077-7.

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Linåker, F., and M. Ishikawa. "Real-time appearance-based Monte Carlo localization." Robotics and Autonomous Systems 54, no. 3 (March 2006): 205–20. http://dx.doi.org/10.1016/j.robot.2005.11.003.

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Lynen, Simon, Bernhard Zeisl, Dror Aiger, Michael Bosse, Joel Hesch, Marc Pollefeys, Roland Siegwart, and Torsten Sattler. "Large-scale, real-time visual–inertial localization revisited." International Journal of Robotics Research 39, no. 9 (July 7, 2020): 1061–84. http://dx.doi.org/10.1177/0278364920931151.

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The overarching goals in image-based localization are scale, robustness, and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both dominated the benchmarks and seen successful real-world deployment. They enable applications ranging from robot navigation, autonomous driving, virtual and augmented reality to device geo-localization. Recently, end-to-end learned localization approaches have been proposed which show promising results on small-scale datasets. However, the positioning accuracy, scalability, latency, and compute and storage requirements of these approaches remain open challenges. We aim to deploy localization at a global scale where one thus relies on methods using local features and sparse 3D models. Our approach spans from offline model building to real-time client-side pose fusion. The system compresses the appearance and geometry of the scene for efficient model storage and lookup leading to scalability beyond what has been demonstrated previously. It allows for low-latency localization queries and efficient fusion to be run in real-time on mobile platforms by combining server-side localization with real-time visual–inertial-based camera pose tracking. In order to further improve efficiency, we leverage a combination of priors, nearest-neighbor search, geometric match culling, and a cascaded pose candidate refinement step. This combination outperforms previous approaches when working with large-scale models and allows deployment at unprecedented scale. We demonstrate the effectiveness of our approach on a proof-of-concept system localizing 2.5 million images against models from four cities in different regions of the world achieving query latencies in the 200 ms range.

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Bald, Christin, and Gerhard Schmidt. "Processing Chain for Localization of Magnetoelectric Sensors in Real Time." Sensors 21, no. 16 (August 23, 2021): 5675. http://dx.doi.org/10.3390/s21165675.

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The knowledge of the exact position and orientation of a sensor with respect to a source (distribution) is essential for the correct solution of inverse problems. Especially when measuring with magnetic field sensors, the positions and orientations of the sensors are not always fixed during measurements. In this study, we present a processing chain for the localization of magnetic field sensors in real time. This includes preprocessing steps, such as equalizing and matched filtering, an iterative localization approach, and postprocessing steps for smoothing the localization outcomes over time. We show the efficiency of this localization pipeline using an exchange bias magnetoelectric sensor. For the proof of principle, the potential of the proposed algorithm performing the localization in the two-dimensional space is investigated. Nevertheless, the algorithm can be easily extended to the three-dimensional space. Using the proposed pipeline, we achieve average localization errors between 1.12 cm and 6.90 cm in a localization area of size 50cm×50cm.

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Han, Seung-Jun, and Jeongdan Choi. "Real-Time Precision Vehicle Localization Using Numerical Maps." ETRI Journal 36, no. 6 (December 1, 2014): 968–78. http://dx.doi.org/10.4218/etrij.14.0114.0040.

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Dissertations / Theses on the topic "Real-time Localization"

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Huang, Yiteng (Arden). "Real-time acoustic source localization with passive microphone arrays." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/15024.

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Lee, Young Jin. "Real-Time Object Motion and 3D Localization from Geometry." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1408443773.

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Dinh, Christoph [Verfasser]. "Brain Monitoring : Real-Time Localization of Neuronal Activity / Christoph Dinh." Aachen : Shaker, 2015. http://d-nb.info/1075437946/34.

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Akhoury, Sharat Saurabh. "Real-Time Localization of Planar Targets on Power-Constrained Devices." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/26162.

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In this thesis we present a method for detecting planar targets in real-time on power-constrained, or low-powered, hand-held devices such as mobile phones. We adopt the feature recognition (also referred to as feature matching) approach and employ fast-to-compute local feature descriptors to establish point correspondences. To obtain a satisfactory localization accuracy, most local feature descriptors seek a transformation of the input intensity patch that is invariant to various geometric and photometric deformations. Generally, such transformations are computationally intensive, hence are not ideal for real-time applications on limited hardware platforms. On the other hand, descriptors which are fast to compute are typically limited in their ability to provide invariance to a vast range of deformations. To address these shortcomings, we have developed a learning-based approach which can be applied to any local feature descriptor to increase the system’s robustness to both affine and perspective deformations. The motivation behind applying a learning-based approach is to transfer as much of the computational burden (as possible) onto an offline training phase, allowing a reduction in cost during online matching. The approach comprises of identifying keypoints which remain stable under artificially induced perspective transformations, extracting the corresponding feature vectors, and finally aggregating the feature vectors of coincident keypoints to obtain the final descriptors. We strictly focus on objects which are planar, thus allowing us to synthesize images of the object in order to capture the appearance of keypoint patches under several perspectives.

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Greene, W. Nicholas (William Nicholas). "Real-time dense simultaneous localization and mapping using monocular cameras." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107051.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 91-100).
Cameras are powerful sensors for robotic navigation as they provide high-resolution environment information (color, shape, texture, etc.), while being lightweight, low-power, and inexpensive. Exploiting such sensor data for navigation tasks typically falls into the realm of monocular simultaneous localization and mapping (SLAM), where both the robot's pose and a map of the environment are estimated concurrently from the imagery produced by a single camera mounted on the robot. This thesis presents a monocular SLAM solution capable of reconstructing dense 3D geometry online without the aid of a graphics processing unit (GPU). The key contribution is a multi-resolution depth estimation and spatial smoothing process that exploits the correlation between low-texture image regions and simple planar structure to adaptively scale the complexity of the generated keyframe depthmaps to the quality of the input imagery. High-texture image regions are represented at higher resolutions to capture fine detail, while low-texture regions are represented at coarser resolutions for smooth surfaces. This approach allows for significant computational savings while simultaneously increasing reconstruction density and quality when compared to the state-of-the-art. Preliminary qualitative results are also presented for an adaptive meshing technique that generates dense reconstructions using only the pixels necessary to represent the scene geometry, which further reduces the computational requirements for fully dense reconstructions.
by W. Nicholas Greene.
S.M.

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Gironés, Sancho Xavier. "Real-Time Localization of Multi-Oriented Text in Natural Scene Images." Doctoral thesis, Universitat Rovira i Virgili, 2021. http://hdl.handle.net/10803/671518.

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Aquesta tesi es centra en el problema de la localització de textos en imatges d'escenes naturals des de la perspectiva de l'eficiència. Amb aquesta finalitat, s'introdueix un mètode de localització de text multiorientat en imatges naturals adequat per al processament en temps real de vídeo d'alta definició en dispositius portàtils i mòbils. El mètode proposat es basa en components connectats (CCs): Primer, els CCs s'aïllen convolucionant la imatge a múltiples escales amb un filtre espacial lineal dissenyat específicament, seguit de binarització amb histèresi. A continuació, els CCs no textuals es filtren emprant una cascada de classificadors locals que operen sobre descriptors expandits incrementalment, on la propietat d'ample de traç s'estima eficientment calculant els quadrats màxims inscrits en els CCs. Els CCs candidats i els seus veïns es verifiquen posteriorment amb un classificador amb context que té en compte els CC de destinació i el seu entorn. Finalment, s'extreuen seqüències de text de totes les escales i després es fusionen utilitzant programació dinàmica. El mètode proposat és capaç de processar vídeo HD de 1080p a gairebé 30 quadres per segon en un ordinador portàtil estàndard sense requerir GPU. A més, en comparatives realitzades en les bases de dades de lectura robusta de ICDAR 2013 i de text d'escena incidental de ICDAR 2015, la solució proposada va rendir més del doble de ràpid que l'estat de la tècnica, a banda de demostrar resultats competitius en termes de precisió i exhaustivitat. A més, aquesta tesi introdueix una nova família d'aproximacions racionals de la funció arctangent vàlides en el rang [0, π / 2] que es pot ampliar fàcilment a dos i quatre quadrants, i una nova tècnica per a la localització de matrícules de vehicles en imatges naturals.
Esta tesis se centra en el problema de la localización de textos en imágenes de escenas naturales desde la perspectiva de la eficiencia. Con este fin, se introduce un método de localización de texto multiorientado en imágenes naturales adecuado para el procesamiento en tiempo real de video de alta definición en dispositivos portátiles y móviles. El método propuesto se basa en el enfoque de componentes conectados (CCs): Primero, los CCs se aíslan convolucionando la imagen a múltiples escalas con un filtro espacial lineal diseñado específicamente, seguido de binarización con histéresis. A continuación, los CCs no textuales se filtran empleando una cascada de clasificadores locales que operan sobre descriptores expandidos incrementalmente, donde la propiedad de ancho de trazo se estima eficientemente calculando los cuadrados máximos inscritos en los CCs. Los CCs candidatos y sus vecinos se verifican posteriormente con un clasificador con contexto que tiene en cuenta los CC de destino y su entorno. Por último, se extraen secuencias de texto en todas las escalas y después se fusionan utilizando programación dinámica. El método propuesto es capaz de procesar video HD de 1080p a casi 30 cuadros por segundo en una computadora portátil estándar sin requerir una GPU. Además, en comparativas realizadas en las bases de datos de lectura robusta de ICDAR 2013 y de texto de escena incidental de ICDAR 2015, la solución propuesta desempeñó más del doble de rápido que el estado de la técnica, aparte de demostrar resultados competitivos en términos de precisión y exhaustividad. Además, esta tesis introduce una nueva familia de aproximaciones racionales de la función arcotangente válida en el rango [0, π / 2] que se puede ampliar fácilmente a dos y cuatro cuadrantes, y una nueva técnica para la localización de matrículas de vehículos en imágenes naturales.
This thesis focuses on the problem of text localization in natural scene images from the perspective of time-efficiency. Towards this end, a multi-oriented text localization method in natural images suitable for real-time processing of high-definition video on portable and mobile devices is introduced. The proposed method is based on the connected component (CC) approach: First, CCs are isolated by convolving a multi-scale pyramid with a specifically designed linear spatial filter, followed by hysteresis thresholding. Next, non-textual CCs are pruned employing a cascade of local classifiers fed with increasingly extended feature vectors, where the stroke width feature is estimated in linear time complexity by computing the maximal inscribed squares in the CCs. Candidate CCs and their neighbors are subsequently checked with a context-aware classifier that takes into account the target CCs and their vicinity. Lastly, text sequences are extracted in all pyramid levels and fused using dynamic programming. The proposed method is capable of processing 1080p HD video at nearly 30 frames per second on a standard laptop without requiring a GPU. Furthermore, when benchmarked on the ICDAR 2013 Robust Reading and on the ICDAR 2015 Incidental Scene Text datasets, it performed more than twice faster than the state-of-the-art, while still delivering competitive results in terms of precision and recall. Additionally, this thesis introduces a new family or rational approximations of the arctangent function valid in the [0, π/2] range that can be easily extended to two and four quadrants, and a new technique for vehicle license plate localization in unconstrained environments is presented as a practical use case leveraging the text localization system described in this research.

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Raja, Asad Khalid. "Fine-grain Indoor Localization Infrastructure for Real-time Inspectionof Large Buildings." Thesis, KTH, Reglerteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-176870.

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This master thesis project is about the systems integration of an indoor localizationsystem using Ultra Wideband Impulse Radio and a drone platform which uses theParrot AR.DRONE 2.0 along with the Robot Operating System (ROS). The goal wasto use o-the-shelf components to integrate an indoor localization system which can beused for energy modelling, indoor environmental panoramas and visual inspection oflarge buildings. The system architecture is explored, implemented and then subjectedto extensive testing. Experimental results of the openRTLS UWB system illustrateaccurate readings down to 2cm for Tag positions. The Parrot AR.DRONE 2.0 waschosen due to its low cost and agility; the open source drivers of ROS ensured modularsystem software, which has room for upgrades. The drone system can be used withoptional additional sensors, either attached internally or externally, to scan indoorareas and form environmental panoramas which can quantify ambient environmentalparameters such as temperature, humidity or pressure in harsh or hard to reach areas.The live video feed from the camera facilitates navigation in NLOS conditions. Thereal time ight path of the Parrot AR.DRONE 2.0 combined with the real time positiondata of the openRTLS UWB-IR system oers a unique insight into ne-grain data oflarge buildings.

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Klüber, Viktor. "Development of a BCI based on real-time neural source localization." Master's thesis, Pontificia Universidad Católica del Perú, 2016. http://tesis.pucp.edu.pe/repositorio/handle/123456789/9519.

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Brain-Computer-Interfaces (BCIs) provide a novel way of communication by interpreting different types of brain states. This principle of reading minds makes BCIs a challenging but at the same time fascinating topic among the different disciplines of electrophysiology and biomedical-signal-processing. This work describes the development of a non-invasive BCI approach using steadystate- visual-evoked-potentials (SSVEP) as a mental strategy. SSVEP based BCIs require an external visual stimulation, which in this work is transmitted by a LCD-screen. Consequently, a visual reactive BCI is integrated as a plug-in into the open source project MNE-CPP, which provides an extensive library for brain monitoring and processing. MNE-Scan, as a standalone software from MNE-CPP, contains the necessary real-time source localization and is used as a framework for the BCI. Moreover, an expansion with a screen keyboard device shows the BCI’s practicability. The work’s result delivers a functioning SSVEP BCI approach with an average detection accuracy of 86 %. However, it is shown, that a transition from a BCI on sensor level to a BCI on source level is challenging and requires a certain pre-development, whereby a first approach of the BCI only was realized on sensor level in this work.
Tesis

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Марченко, Ігор Олександрович, Игорь Александрович Марченко, Ihor Oleksandrovych Marchenko, Сергій Олександрович Петров, Сергей Александрович Петров, Serhii Oleksandrovych Petrov, and A. A. Pidkuiko. "Usage of keypoint descriptors based algorithms for real-time objects localization." Thesis, Центральноукраїнський національний технічний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/68603.

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In order to achieve high level of security in our everyday life we produce huge amount of data. Significant part of information is presented by videos, sounds or images. A computer is used to extract useful information from raw data [1]. Pattern recognition is branch of computer vision, which allows us to get information from images [2] and videos. Information extraction is crucial problem of pattern recognition. This problem is divided into next branches: object presence; object localization; object classification.

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GARRAFFA, Giovanni. "Real Time Localization Systems for autonomous navigation: Modelling, Analysis and Control." Doctoral thesis, Università degli Studi di Palermo, 2021. http://hdl.handle.net/10447/514955.

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Questo lavoro di tesi riguarda la derivazione di osservatori ibridi dello stato, analisi e controllo, di sistemi di localizzazione e navigazione in tempo reale (RTLS). In particolare, il framework dei sistemi ibridi è stato utilizzato per tener conto delle dinamiche continue e discrete coinvolte nel processo di stima e della natura sporadica e tempo randomica delle misure provenienti da vari sensori di distanza e/o inerziali. Analisi di convergenza sono state effettuate per dimostrare la stabilità delle soluzioni proposte e la capacità di filtraggio dei rumori presenti nelle misure. Il presente lavoro è corredato dai risultati delle prove sperimentali di laboratorio a conferma della validità delle soluzioni proposte.
This thesis work concerns the derivation of hybrid state observers, analysis and control, of real-time localization and navigation systems (RTLS). In particular, the hybrid systems framework was used to take into account the continuous and discrete dynamics involved in the estimation process and the sporadic and time-random nature of the measurements from various distance and / or inertial sensors. Convergence analyzes were carried out to demonstrate the stability of the proposed solutions and the filtering capacity of the noises present in the measurements. This work is accompanied by the results of the experimental laboratory tests confirming the validity of the proposed solutions.

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Books on the topic "Real-time Localization"

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Wahdan, Mahmoud A. New motion planning and real-time localization methods using proximity for autonomous mobile robots. Monterey, Calif: Naval Postgraduate School, 1996.

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New Motion Planning and Real-Time Localization Methods Using Proximity for Autonomous Mobile Robots. Storming Media, 1996.

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Peng, Philip W. H. Shoulder Injections: Ultrasound. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199908004.003.0043.

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This chapter reviews the anatomy and ultrasound-guided techniques of various shoulder injections, including the glenohumeral joints, subacromial subdeltoid bursa, long head of biceps, and acromioclavicular joint. Ultrasonography is a very useful tool allowing accurate localization of the various target structures for shoulder injections and real-time guidance of the needle insertion. A good understanding of the anatomy and sonoanatomy is of paramount importance in performing the ultrasound-guided injections.

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Berrill, Andrew, and Pawan Gupta. General principles of regional anaesthesia. Edited by Philip M. Hopkins. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0052.

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Regional anaesthesia is now extremely safe in experienced hands. The vast majority of upper and lower limb procedures can now be performed with either a peripheral regional block alone or in combination with a general anaesthetic. Neuraxial blocks can provide reliable postoperative pain relief for operations on the trunk and lower limbs. There is no consensus on the maximum safe dose of local anaesthetics. It is important therefore to use a minimum optimal dose of a local anaesthetic for any nerve block to reduce the risk of toxicity and to improve the success rate. Adjuncts, such as clonidine and dexamethasone, can prolong the duration of the block. Advances in nerve localization methods and block needles have further improved the safety of nerve blocks. There is increasing evidence to show that ultrasound is superior to peripheral nerve stimulation for identifying nerves. Ultrasound also helps in real-time visualization of the spread of the local anaesthetic. Consent, sedation, and support from non-anaesthetic staff play a key role in the success of regional anaesthesia, especially in awake patients. Although serious complications from nerve blocks are uncommon, direct nerve injury is perhaps the most serious complication. Fortunately, these symptoms in the overwhelming majority resolve within a year. This chapter covers the history, factors affecting local anaesthetics, role of adjuncts, nerve localization techniques, and complications of regional anaesthesia. Finally, some suggestions to improve the success and safety of peripheral nerve blocks are discussed.

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Dyer, Paul S., Carol A. Munro, and Rosie E. Bradshaw. Fungal genetics. Edited by Christopher C. Kibbler, Richard Barton, Neil A. R. Gow, Susan Howell, Donna M. MacCallum, and Rohini J. Manuel. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198755388.003.0005.

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Fungi have been long used as model organisms to investigate genetic and cellular processes. An overview is provided of how fungi function at a genetic level, including ploidy, gene structure, and gene flow by sexual and asexual processes. The tools used to study fungal genetics are then described, such techniques having widespread applications in medical mycology research. Classical genetic analysis includes the use of gene mapping by sexual crossing and tetrad analysis, and forward genetic experimentation based on mutagenesis, for which various mutant screening approaches are described. Molecular genetic analysis includes gene manipulation by transformation; different methods for gene knockout and targeting, and their application for forward and reverse genetic approaches, are outlined. Finally, molecular genetic methods used to study gene expression and function are reviewed, including use of inducible or constitutive overexpression, real-time PCR, cellular localization of gene products by fluorescent tagging, and detection of protein–protein interactions.

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Roberts, Timothy P. L., and Luke Bloy. Neuroimaging in Pediatric Psychiatric Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0060.

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Noninvasive imaging and electrophysiological techniques have been developed to probe specific aspects of brain function and dysfunction, providing exquisite spatial maps of functional centers and temporal characteristics. The evolution of these techniques has advanced from single-modality methods identifying functional localization, specialization and segregation, through real-time measures of neuronal activity, toward multimodality integration of structural, functional, and spectro-temporal approaches. While these have an immediate impact in conditions where physical brain lesions are evident (e.g., brain tumor and stroke), making a commensurate contribution within neuropsychiatry is more complex. Nonetheless, by combining concepts of morphology, neurochemistry, neural signal propagation, and regional connectivity, there appears to be ample opportunity to contribute not only to the diagnosis of patients with mental illness but to the stratification and subtyping across behavioral phenotypes and, ultimately, to patient management. Here we present an overview of the most common noninvasive neuroimaging methodologies and their applications to pediatric neurodevelopmental disorders.

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Book chapters on the topic "Real-time Localization"

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Bourdon, Benoit, Jean-Jacques Boye, Quentin Descours, Bastien Drouot, Olivier Reynet, and Thibault Viravau. "SWARMON—Real-Time Localization System." In Robotic Sailing 2015, 113–22. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23335-2_9.

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Poulopoulos, Nikolaos, and Emmanouil Z. Psarakis. "Real Time Eye Localization and Tracking." In Advances in Service and Industrial Robotics, 560–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00232-9_59.

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Conti, Massimo. "Real Time Localization Using Bluetooth Low Energy." In Bioinformatics and Biomedical Engineering, 584–95. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56154-7_52.

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Grzejszczak, Tomasz, Jakub Nalepa, and Michal Kawulok. "Real-Time Wrist Localization in Hand Silhouettes." In Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, 439–49. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00969-8_43.

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Dobrovodský, Karol, and Pavel Andris. "Real Time Sub Image Localization for Tracking." In Advances in Service and Industrial Robotics, 588–96. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00232-9_62.

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Speck, Daniel, Marc Bestmann, and Pablo Barros. "Towards Real-Time Ball Localization Using CNNs." In RoboCup 2018: Robot World Cup XXII, 337–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27544-0_28.

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Zhao, Zhongliang, Jose Carrera, Joel Niklaus, and Torsten Braun. "Machine Learning-Based Real-Time Indoor Landmark Localization." In Lecture Notes in Computer Science, 95–106. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02931-9_8.

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Kornatowski, Eugeniusz. "Localization of Sound Source Direction in Real Time." In Advances in Intelligent and Soft Computing, 39–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14989-4_4.

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Rajasundari, T., A. Balaji Ganesh, A. Hari Prakash, V. Ramji, and A. Lakshmi Sangeetha. "Improved WiFi Based Real-Time Indoor Localization Strategy." In Intelligent Data Communication Technologies and Internet of Things, 84–95. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34080-3_10.

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Charles, Subodha, and Prabhat Mishra. "Real-Time Detection and Localization of DoS Attacks." In Network-on-Chip Security and Privacy, 183–217. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69131-8_8.

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Conference papers on the topic "Real-time Localization"

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Badino, Hernan, Daniel Huber, and Takeo Kanade. "Real-time topometric localization." In 2012 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2012. http://dx.doi.org/10.1109/icra.2012.6224716.

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Chawla, Kirti, Christopher McFarland, Gabriel Robins, and Connor Shope. "Real-time RFID localization using RSS." In 2013 International Conference on Localization and GNSS (ICL-GNSS). IEEE, 2013. http://dx.doi.org/10.1109/icl-gnss.2013.6577259.

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Jaworski, Wojciech, Pawel Wilk, Pawel Zborowski, Witold Chmielowiec, Andrew YongGwon Lee, and Abhishek Kumar. "Real-time 3D indoor localization." In 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2017. http://dx.doi.org/10.1109/ipin.2017.8115874.

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Xu Huiyan and Wang Jingfang. "Real-time iris localization method." In 2011 International Conference on Image Analysis and Signal Processing (IASP). IEEE, 2011. http://dx.doi.org/10.1109/iasp.2011.6109058.

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Mandlik, Michal, Zdenek Nemec, and Radovan Dolecek. "Real-time sound source localization." In 2012 13th International Radar Symposium (IRS). IEEE, 2012. http://dx.doi.org/10.1109/irs.2012.6233370.

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Werner-Allen, Geoffrey, Patrick Swieskowski, and Matt Welsh. "Real-time volcanic earthquake localization." In the 4th international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1182807.1182853.

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Paakki, Tommi, and Jari Nurmi. "Faster than real-time GNSS receiver testing." In 2014 International Conference on Localization and GNSS (ICL-GNSS). IEEE, 2014. http://dx.doi.org/10.1109/icl-gnss.2014.6934172.

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Mouragnon, E., M. Lhuillier, M. Dhome, F. Dekeyser, and P. Sayd. "Real Time Localization and 3D Reconstruction." In 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06). IEEE, 2006. http://dx.doi.org/10.1109/cvpr.2006.236.

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Gietler, Harald, and Hubert Zangl. "A Real-time Electromagnetic Localization System." In 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2022. http://dx.doi.org/10.1109/i2mtc48687.2022.9806498.

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Gupta, Ashish, and Alper Yilmaz. "Ubiquitous real-time geo-spatial localization." In SIGSPATIAL'16: 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/3005422.3005426.

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Reports on the topic "Real-time Localization"

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Peterson, J. M., and Chris Kyriakakis. Hybrid Algorithm for Robust, Real-Time Source Localization in Reverberant Environments. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada459061.

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Dugan, Peter J., Christopher W. Clark, Yann A. LeCun, and Sofie M. Van Parijs. DCL System Research Using Advanced Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada572279.

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Dugan, Peter J., Christopher W. Clark, Yann A. LeCun, and Sofie M. Van Parijs. DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada573473.

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Dugan, Peter J., Christopher W. Clark, Yann A. LeCun, and Sofie M. Van Parijs. DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada617980.

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Rahmani, Mehran, Xintong Ji, and Sovann Reach Kiet. Damage Detection and Damage Localization in Bridges with Low-Density Instrumentations Using the Wave-Method: Application to a Shake-Table Tested Bridge. Mineta Transportation Institute, September 2022. http://dx.doi.org/10.31979/mti.2022.2033.

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This study presents a major development to the wave method, a methodology used for structural identification and monitoring. The research team tested the method for use in structural damage detection and damage localization in bridges, the latter being a challenging task. The main goal was to assess capability of the improved method by applying it to a shake-table-tested prototype bridge with sparse instrumentation. The bridge was a 4-span reinforced concrete structure comprising two columns at each bent (6 columns total) and a flat slab. It was tested to failure using seven biaxial excitations at its base. Availability of a robust and verified method, which can work with sparse recording stations, can be valuable for detecting damage in bridges soon after an earthquake. The proposed method in this study includes estimating the shear (cS) and the longitudinal (cL) wave velocities by fitting an equivalent uniform Timoshenko beam model in impulse response functions of the recorded acceleration response. The identification algorithm is enhanced by adding the model’s damping ratio to the unknown parameters, as well as performing the identification for a range of initial values to avoid early convergence to a local minimum. Finally, the research team detect damage in the bridge columns by monitoring trends in the identified shear wave velocities from one damaging event to another. A comprehensive comparison between the reductions in shear wave velocities and the actual observed damages in the bridge columns is presented. The results revealed that the reduction of cS is generally consistent with the observed distribution and severity of damage during each biaxial motion. At bents 1 and 3, cS is consistently reduced with the progression of damage. The trends correctly detected the onset of damage at bent 1 during biaxial 3, and damage in bent 3 during biaxial 4. The most significant reduction was caused by the last two biaxial motions in bents 1 and 3, also consistent with the surveyed damage. In bent 2 (middle bent), the reduction trend in cS was relatively minor, correctly showing minor damage at this bent. Based on these findings, the team concluded that the enhanced wave method presented in this study was capable of detecting damage in the bridge and identifying the location of the most severe damage. The proposed methodology is a fast and inexpensive tool for real-time or near real-time damage detection and localization in similar bridges, especially those with sparsely deployed accelerometers.

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Ghanim, Murad, Joe Cicero, Judith K. Brown, and Henryk Czosnek. Dissection of Whitefly-geminivirus Interactions at the Transcriptomic, Proteomic and Cellular Levels. United States Department of Agriculture, February 2010. http://dx.doi.org/10.32747/2010.7592654.bard.

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Our project focuses on gene expression and proteomics of the whitefly Bemisia tabaci (Gennadius) species complex in relation to the internal anatomy and localization of expressed genes and virions in the whitefly vector, which poses a major constraint to vegetable and fiber production in Israel and the USA. While many biological parameters are known for begomovirus transmission, nothing is known about vector proteins involved in the specific interactions between begomoviruses and their whitefly vectors. Identifying such proteins is expected to lead to the design of novel control methods that interfere with whitefly-mediated begomovirus transmission. The project objectives were to: 1) Perform gene expression analyses using microarrays to study the response of whiteflies (B, Q and A biotypes) to the acquisition of begomoviruses (Tomato yellow leaf curl (TYLCV) and Squash leaf curl (SLCV). 2) Construct a whitefly proteome from whole whiteflies and dissected organs after begomovirus acquisition. 3) Validate gene expression by q-RTPCR and sub-cellular localization of candidate ESTs identified in microarray and proteomic analyses. 4) Verify functionality of candidate ESTs using an RNAi approach, and to link these datasets to overall functional whitefly anatomical studies. During the first and second years biological experiments with TYLCV and SLCV acquisition and transmission were completed to verify the suitable parameters for sample collection for microarray experiments. The parameters were generally found to be similar to previously published results by our groups and others. Samples from whole whiteflies and midguts of the B, A and Q biotypes that acquired TYLCV and SLCV were collected in both the US and Israel and hybridized to B. tabaci microarray. The data we analyzed, candidate genes that respond to both viruses in the three tested biotypes were identified and their expression that included quantitative real-time PCR and co-localization was verified for HSP70 by the Israeli group. In addition, experiments were undertaken to employ in situ hybridization to localize several candidate genes (in progress) using an oligonucleotide probe to the primary endosymbiont as a positive control. A proteome and corresponding transcriptome to enable more effective protein identification of adult whiteflies was constructed by the US group. Further validation of the transmission route of begomoviruses, mainly SLCV and the involvement of the digestive and salivary systems was investigated (Cicero and Brown). Due to time and budget constraints the RNAi-mediated silencing objective to verify gene function was not accomplished as anticipated. HSP70, a strong candidate protein that showed over-expression after TYLCV and SLCV acquisition and retention by B. tabaci, and co-localization with TYLCV in the midgut, was further studies. Besides this protein, our joint research resulted in the identification of many intriguing candidate genes and proteins that will be followed up by additional experiments during our future research. To identify these proteins it was necessary to increase the number and breadth of whitefly ESTs substantially and so whitefly cDNAs from various libraries made during the project were sequenced (Sanger, 454). As a result, the proteome annotation (ID) was far more successful than in the initial attempt to identify proteins using Uniprot or translated insect ESTs from public databases. The extent of homology shared by insects in different orders was surprisingly low, underscoring the imperative need for genome and transcriptome sequencing of homopteran insects. Having increased the number of EST from the original usable 5500 generated several years ago to >600,000 (this project+NCBI data mining), we have identified about one fifth of the whitefly proteome using these new resources. Also we have created a database that links all identified whitefly proteins to the PAVEdb-ESTs in the database, resulting in a useful dataset to which additional ESTS will be added. We are optimistic about the prospect of linking the proteome ID results to the transcriptome database to enable our own and other labs the opportunity to functionally annotate not only genes and proteins involved in our area of interest (whitefly mediated transmission) but for the plethora of other functionalities that will emerge from mining and functionally annotating other key genes and gene families in whitefly metabolism, development, among others. This joint grant has resulted in the identification of numerous candidate proteins involved in begomovirus transmission by B. tabaci. A next major step will be to capitalize on validated genes/proteins to develop approaches to interfere with the virus transmission.

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved.

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