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Добірка наукової літератури з теми "Particles tracking"

Автор: Grafiati

Опубліковано: 3 травня 2025

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Статті в журналах з теми "Particles tracking"

Jones, Benjamin T., Andrew Solow, and Rubao Ji. "Resource Allocation for Lagrangian Tracking." Journal of Atmospheric and Oceanic Technology 33, no. 6 (June 2016): 1225–35. http://dx.doi.org/10.1175/jtech-d-15-0115.1.

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AbstractAccurate estimation of the transport probabilities among regions in the ocean provides valuable information for understanding plankton transport, the spread of pollutants, and the movement of water masses. Individual-based particle-tracking models simulate a large ensemble of Lagrangian particles and are a common method to estimate these transport probabilities. Simulating a large ensemble of Lagrangian particles is computationally expensive, and appropriately allocating resources can reduce the cost of this method. Two universal questions in the design of studies that use Lagrangian particle tracking are how many particles to release and how to distribute particle releases. A method is presented for tailoring the number and the release location of particles to most effectively achieve the objectives of a study. The method detailed here is a sequential analysis procedure that seeks to minimize the number of particles that are required to satisfy a predefined metric of result quality. The study assesses the result quality as the precision of the estimates for the elements of a transport matrix and also describes how the method may be extended for use with other metrics. Applying this methodology to both a theoretical system and a particle transport model of the Gulf of Maine results in more precise estimates of the transport probabilities with fewer particles than from uniformly or randomly distributing particle releases. The application of this method can help reduce the cost of and increase the robustness of results from studies that use Lagrangian particles.

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Zhang, Lieping, Jinghua Nie, Shenglan Zhang, Yanlin Yu, Yong Liang, and Zuqiong Zhang. "Research on the Particle Filter Single-Station Target Tracking Algorithm Based on Particle Number Optimization." Journal of Electrical and Computer Engineering 2021 (September 4, 2021): 1–8. http://dx.doi.org/10.1155/2021/2838971.

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Given that the tracking accuracy and real-time performance of the particle filter (PF) target tracking algorithm are greatly affected by the number of sampled particles, a PF target tracking algorithm based on particle number optimization under the single-station environment was proposed in this study. First, a single-station target tracking model was established, and the corresponding PF algorithm was designed. Next, a tracking simulation experiment was carried out on the PF target tracking algorithm under different numbers of particles with the root mean square error (RMSE) and filtering time as the evaluation indexes. On this basis, the optimal number of particles, which could meet the accuracy and real-time performance requirements, was determined and taken as the number of particles of the proposed algorithm. The MATLAB simulation results revealed that compared with the unscented Kalman filter (UKF), the single-station PF target tracking algorithm based on particle number optimization not only was of high tracking accuracy but also could meet the real-time performance requirement.

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Siradjuddin, Indah Agustien, and Muhammad Rahmat Widyanto. "Particle Filter with Gaussian Weighting for Vehicle Tracking." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 6 (August 20, 2011): 681–86. http://dx.doi.org/10.20965/jaciii.2011.p0681.

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To track vehicle motion in data video, particle filter with Gaussian weighting is proposed. This method consists of four main stages. First, particles are generated to predict target’s location. Second, certain particles are searched and these particles are used to build Gaussian distribution. Third, weight of all particles is calculated based on Gaussian distribution. Fourth, particles are updated based on each weight. The proposed method could reduce computational time of tracking compared to that of conventional method of particle filter, since the proposed method does not have to calculate all particles weight using likelihood function. This method has been tested on video data with car as a target object. In average, this proposed method of particle filter is 60.61% times faster than particle filter method meanwhile the accuracy of tracking with this newmethod is comparable with particle filter method, which reach up to 86.87%. Hence this method is promising for real time object tracking application.

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Sun, Qi Yuan, Liu Sheng Li, and Zuo Liang Chao. "Target Tracking Based on Particle Filter with Multi-Path Particles." Applied Mechanics and Materials 130-134 (October 2011): 3306–10. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.3306.

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Visual tracking is a key issue for autonomous navigation, intelligent monitoring system and so on. While a Particle Filter for tracking is designed, the target in image may be out of range, and the tracked target will be lost since the target image size keeps changing. A method for tracking a mobile target with visual image, Particle Filter with multi-path particles (PFWMP), is proposed to solve the above problem in this paper. Here, the method is based on the wavelet transform incorporated in traditional Particle Filter, and particles are made to move in original image and the image processed by wavelet transform. The results show that the improved approach using multiple particles can enhance the robustness of tracking algorithm and improve tracking accuracy.

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Li, Tao, and Qi Yuan Sun. "A Visual Tracking Based on Particle Filter of Multi-Algorithm Fusion." Applied Mechanics and Materials 513-517 (February 2014): 2893–96. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2893.

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A novel visual tracking algorithm based on particle filter with multi-algorithm fusion is proposed. Mean shift is employed to make particles distribute more reasonably in order to maintain tracking accuracy by using fewer particles, and the genetic evolution ideas is introduced to increase the diversity of samples by applying selection, crossover and mutation operator to achieve particles resampling. The experiments show that the tracking performance of the proposed method, compared with Mean Shift Embedded Particle Filter (MSEPF), is significantly improved.

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Wang, Lian-Ping, and D. E. Stock. "Numerical Simulation of Heavy Particle Dispersion Time Step and Nonlinear Drag Considerations." Journal of Fluids Engineering 114, no. 1 (March 1, 1992): 100–106. http://dx.doi.org/10.1115/1.2909983.

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Numerical experiments can be used to study heavy particle dispersion by tracking particles through a numerically generated instantaneous turbulent flow field. In this manner, data can be generated to supplement physical experiments. To perform the numerical experiments efficiently and accurately, the time step used when tracking the particles through the fluid must be chosen correctly. After finding a suitable time step for one particular simulation, the time step must be reduced as the total integration time increases and as the free-fall velocity of the particle increases. Based on the numerical calculations, we suggest that the nonlinear drag be included in a numerical simulation if the ratio of the particle’s Stokes free-fall velocity to the fluid rms velocity is greater than two.

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Müller, Dennis, Andreas Rausch, Olga Dolnik, and Thomas Schanze. "Comparing human and algorithmic tracking of subviral particles in fluorescence microscopic image sequences." Current Directions in Biomedical Engineering 3, no. 2 (September 7, 2017): 543–47. http://dx.doi.org/10.1515/cdbme-2017-0114.

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AbstractTracking of subviral particles with automated methods enables the analysis of intracellular processes exhibited by viruses. A linear assignment problem solver and a Kalman-filter have been added to an existing particle tracking algorithm. First results produced with simulated image sequences showed that the improved algorithm is able to improve tracking results by closing gaps in the particle’s trajectories. Here we report on the evaluation of the LAP-Kalman algorithm using real fluorescence-microscopic images. The results from the original and improved algorithm have been compared to the results of manual tracking. Evaluation results indicate that the improved algorithm is capable to reconstruct missing parts of particle tracks in difficult conditions. However, the evaluation of the algorithms and the manual tracking is a complex task because of the low image contrast and high object density with intersecting tracks in the live-cell images.

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Yao, Hai Tao, Hai Qiang Chen, and Tuan Fa Qin. "Niche PSO Particle Filter with Particles Fusion for Target Tracking." Applied Mechanics and Materials 239-240 (December 2012): 1368–72. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1368.

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An improved particle filter algorithm is proposed to track a randomly moving target in video. In particle filter framework, a particle swarm optimization improved by niche technique which implemented by restricted competition selection is integrated. It can move particles into high likelihood area of target and form multi-population distribution, so that the searching capability of particles is enhanced and then the adaptation to the change of dynamic target state is improved. The particles of niching particle swarm optimization and the particles of particle filter are integrated for new particle weight calculation and finally realize a new particle filter for target tracking in video sequence.

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Zhu, Hong Bo, Hai Zhao, Dan Liu, and Chun He Song. "Compressed Iterative Particle Filter for Target Tracking." Applied Mechanics and Materials 55-57 (May 2011): 91–94. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.91.

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Particle filtering has been widely used in the non-linear n-Gaussian target tracking problems. The main problem of particle filtering is the lacking and exhausting of particles, and choosing effective proposed distribution is the key point to overcome it. In this paper, a new mixed particle filtering algorithm was proposed. Firstly, the unscented kalman filtering is used to generate the proposed distribution, and in the resample step, a new certain resample method is used to choose the particles with ordered larger weights. GA algorithm is introduced into the certain resample method to keep the variety of the particles. Simuational results have shown that the proposed algorithm has better performances than other three typical filtering algorithms.

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Chen, Zhimin, Mengchu Tian, Yuming Bo, and Xiaodong Ling. "Infrared small target detection and tracking algorithm based on new closed-loop control particle filter." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 4 (January 30, 2018): 1435–56. http://dx.doi.org/10.1177/0954410017753445.

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The problem of particle impoverishment could be always found in standard particle filter, additionally a large number of particles are required for accurate estimation. as it is difficult to meet the demand of modern infrared search and tracking system. To solve this problem, an improved infrared small target detection and tracking method based on closed-loop control bat algorithm optimized particle filter is proposed. Firstly, bat algorithm is introduced into the particle filtering in this method. Particles are used to simulate the process that an individual bat hunts and avoids obstacles so that particles move towards the high-likelihood region. Meanwhile, the improved algorithm takes the proportion of particles accepting a new state as the feedback quantity and proposes to conduct dynamic control on global and local search ability of particle filtering by closed-loop control strategy, which further improves the overall quality of particle distribution. The performance of the improved detection and tracking algorithm is tested in simulation scene and real scene of infrared small target. Experimental results show that the improved algorithm improves the performance of the infrared searching and tracking system.

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Дисертації з теми "Particles tracking"

Hosack, Michael G. "Optimization of particle tracking for experiment E683 at Fermi National Laboratory." Virtual Press, 1995. http://liblink.bsu.edu/uhtbin/catkey/941370.

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The subject of this thesis is the improvement of particle tracking through the identification and correction of small systematic errors in particle "hit" locations due to positioning of tracking detectors. These errors call be as large or larger than the statistical spatial resolution of tracking detectors themselves, and therefore must be corrected. The focus is on identification and correction of errors due to rotations and beam axis translations.An algorithm is developed for use with proportional wire chamber and drift chamber detectors in experiment E683 at the Wideband facility of Fermi National Laboratory. In this experiment, high energy (tens of GeV) particles, primarily mesons, were produced when photons with energies of 40-400 GeV struck a metal or liquid target.At the present time, the method and code developed for this thesis has not been applied to real data, although an analysis of its effectiveness as a function of detector resolution has been investigated with Monte-Carlo simulations.
Department of Physics and Astronomy

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Huck, Peter Dearborn. "Particle dynamics in turbulence : from the role of inhomogeneity and anisotropy to collective effects." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEN073/document.

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La turbulence est connue pour sa capacité à disperser efficacement de la matière, que ce soit des polluantes dans les océans ou du carburant dans les moteurs à combustion. Deux considérations essentielles s’imposent lorsqu’on considère de telles situations. Primo, l’écoulement sous-jacente pourrait avoir une influence non-négligeable sur le comportement des particules. Secundo, la concentration locale de la matière pourrait empêcher le transport ou l’augmenter. Pour répondre à ces deux problématiques distinctes, deux dispositifs expérimentaux ont été étudiés au cours de cette thèse. Un premier dispositif a été mis en place pour étudier l’écoulement de von Kàrmàn, qui consiste en une enceinte fermé avec de l’eau forcé par deux disques en contra-rotation. Cette écoulement est connu pour être très turbulent, inhomogène, et anisotrope. Deux caméras rapides ont facilité le suivi Lagrangien des particules isodenses avec l’eau et petites par rapport aux échelles de la turbulence. Ceci a permis une étude du bilan d’énergie cinétique turbulente qui est directement relié aux propriétés de transport. Des particules plus lourdes que l’eau ont aussi été étudiées et montrent le rôle de l’anisotropie de l’écoulement dans la dispersion des particules inertielles. Un deuxième dispositif, un écoulement de soufflerie ensemencé avec des gouttelettes d’eau micrométriques a permis une étude de l’effet de la concentration locale de l’eau sur la vitesse de chute des gouttelettes grâce à une montage préexistant. Un modèle basé sur des méthodes théorique d'écoulements multiphasiques a été élaboré enfin de prendre en compte les effets collectifs de ces particules sedimentant dans un écoulement turbulent. Les résultats théoriques et expérimentaux mettent en évidence le rôle de la polydispersité et du couplage entre les deux phases dans l’augmentation de la sédimentation des gouttelettes
Turbulence is well known for its ability to efficiently disperse matter, whether it be atmospheric pollutants or gasoline in combustion motors. Two considerations are fundamental when considering such situations. First, the underlying flow may have a strong influence of the behavior of the dispersed particles. Second, the local concentration of particles may enhance or impede the transport properties of turbulence. This dissertation addresses these points separately through the experimental study of two different turbulent flows. The first experimental device used is the so-called von K\'arm\'an flow which consists of an enclosed vessel filled with water that is forced by two counter rotating disks creating a strongly inhomogeneous and anisotropic turbulence. Two high-speed cameras permitted the creation a trajectory data base particles that were both isodense and heavier than water but were smaller than the smallest turbulent scales. The trajectories of this data base permitted a study of the turbulent kinetic energy budget which was shown to directly related to the transport properties of the turbulent flow. The heavy particles illustrate the role of flow anisotropy in the dispersive dynamics of particles dominated by effects related to their inertia. The second flow studied was a wind tunnel seeded with micrometer sized water droplets which was used to study the effects of local concentration of the settling velocities of these particles. A model based on theoretical multi-phase methods was developed in order to take into account the role of collective effects on sedimentation in a turbulent flow. The theoretical results emphasize the role of coupling between the underlying flow and the dispersed phase

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Magnusson, Klas E. G. "Segmentation and tracking of cells and particles in time-lapse microscopy." Doctoral thesis, KTH, Signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-196911.

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In biology, many different kinds of microscopy are used to study cells. There are many different kinds of transmission microscopy, where light is passed through the cells, that can be used without staining or other treatments that can harm the cells. There is also fluorescence microscopy, where fluorescent proteins or dyes are placed in the cells or in parts of the cells, so that they emit light of a specific wavelength when they are illuminated with light of a different wavelength. Many fluorescence microscopes can take images on many different depths in a sample and thereby build a three-dimensional image of the sample. Fluorescence microscopy can also be used to study particles, for example viruses, inside cells. Modern microscopes often have digital cameras or other equipment to take images or record time-lapse video. When biologists perform experiments on cells, they often record image sequences or sequences of three-dimensional volumes to see how the cells behave when they are subjected to different drugs, culture substrates, or other external factors. Previously, the analysis of recorded data has often been done manually, but that is very time-consuming and the results often become subjective and hard to reproduce. Therefore there is a great need for technology for automated analysis of image sequences with cells and particles inside cells. Such technology is needed especially in biological research and drug development. But the technology could also be used clinically, for example to tailor a cancer treatment to an individual patient by evaluating different treatments on cells from a biopsy. This thesis presents algorithms to find cells and particles in images, and to calculate tracks that show how they have moved during an experiment. We have developed a complete system that can find and track cells in all commonly used imaging modalities. We selected and extended a number of existing segmentation algorithms, and thereby created a complete tool to find cell outlines. To link the segmented objects into tracks, we developed a new track linking algorithm. The algorithm adds tracks one by one using dynamic programming, and has many advantages over prior algorithms. Among other things, it is fast, it calculates tracks which are optimal for the entire image sequence, and it can handle situations where multiple cells have been segmented incorrectly as one object. To make it possible to use information about the velocities of the objects in the linking, we developed a method where the positions of the objects are preprocessed using a filter before the linking is performed. This is important for tracking of some particles inside cells and for tracking of cell nuclei in some embryos. We have developed an open source software which contains all tools that are necessary to analyze image sequences with cells or particles. It has tools for segmentation and tracking of objects, optimization of settings, manual correction, and analysis of outlines and tracks. We developed the software together with biologists who used it in their research. The software has already been used for data analysis in a number of biology publications. Our system has also achieved outstanding performance in three international objective comparisons of systems for tracking of cells.
Inom biologi används många olika typer av mikroskopi för att studera celler. Det finns många typer av genomlysningsmikroskopi, där ljus passerar genom cellerna, som kan användas utan färgning eller andra åtgärder som riskerar att skada cellerna. Det finns också fluorescensmikroskopi där fluorescerande proteiner eller färger förs in i cellerna eller i delar av cellerna, så att de emitterar ljus av en viss våglängd då de belyses med ljus av en annan våglängd. Många fluorescensmikroskop kan ta bilder på flera olika djup i ett prov och på så sätt bygga upp en tre-dimensionell bild av provet. Fluorescensmikroskopi kan även användas för att studera partiklar, som exempelvis virus, inuti celler. Moderna mikroskop har ofta digitala kameror eller liknande utrustning för att ta bilder och spela in bildsekvenser. När biologer gör experiment på celler spelar de ofta in bildsekvenser eller sekvenser av tre-dimensionella volymer för att se hur cellerna beter sig när de utsätts för olika läkemedel, odlingssubstrat, eller andra yttre faktorer. Tidigare har analysen av inspelad data ofta gjorts manuellt, men detta är mycket tidskrävande och resultaten blir ofta subjektiva och svåra att reproducera. Därför finns det ett stort behov av teknik för automatiserad analys av bildsekvenser med celler och partiklar inuti celler. Sådan teknik behövs framförallt inom biologisk forskning och utveckling av läkemedel. Men tekniken skulle också kunna användas kliniskt, exempelvis för att skräddarsy en cancerbehandling till en enskild patient genom att utvärdera olika behandlingar på celler från en biopsi. I denna avhandling presenteras algoritmer för att hitta celler och partiklar i bilder, och för att beräkna trajektorier som visar hur de har förflyttat sig under ett experiment. Vi har utvecklat ett komplett system som kan hitta och följa celler i alla vanligt förekommande typer av mikroskopi. Vi valde ut och vidareutvecklade ett antal existerande segmenteringsalgoritmer, och skapade på så sätt ett heltäckande verktyg för att hitta cellkonturer. För att länka ihop de segmenterade objekten till trajektorier utvecklade vi en ny länkningsalgoritm. Algoritmen lägger till trajektorier en och en med hjälp av dynamisk programmering, och har många fördelar jämfört med tidigare algoritmer. Bland annat är den snabb, den beräknar trajektorier som är optimala över hela bildsekvensen, och den kan hantera fall då flera celler felaktigt segmenterats som ett objekt. För att kunna använda information om objektens hastighet vid länkningen utvecklade vi en metod där objektens positioner förbehandlas med hjälp av ett filter innan länkningen utförs. Detta är betydelsefullt för följning av vissa partiklar inuti celler och för följning av cellkärnor i vissa embryon. Vi har utvecklat en mjukvara med öppen källkod, som innehåller alla verktyg som krävs för att analysera bildsekvenser med celler eller partiklar. Den har verktyg för segmentering och följning av objekt, optimering av inställningar, manuell korrektion, och analys av konturer och trajektorier. Vi utvecklade mjukvaran i samarbete med biologer som använde den i sin forskning. Mjukvaran har redan använts för dataanalys i ett antal biologiska publikationer. Vårt system har även uppnått enastående resultat i tre internationella objektiva jämförelser av system för följning av celler.

QC 20161125

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Veerasamy, Saravanan. "Valdiation of BaBar tracking software using lambda hyperon." Thesis, University of Iowa, 2007. http://ir.uiowa.edu/etd/141.

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Trenkmann, Ines, Daniela Täuber, Michael Bauer, Jörg Schuster, Sangho Bok, Shubhra Gangopadhyay, and Christian von Borczyskowski. "Investigations of solid liquid interfaces in ultra-thin liquid films via single particle tracking of silica particles." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-191734.

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Single particle tracking with a wide field microscope is used to study the solid liquid interface between the viscous liquid tetrakis(2 ethylhexoxy)-silane and a silicon dioxide surface. Silicon dioxide nanoparticles (5 nm diameter) marked with the fluorescent dye rhodamine 6G are used as probes. The distributions of diffusion coefficients, obtained by mean squared displacements, reveal heterogeneities with at least two underlying diffusion components. Measurements on films with varying film thicknesses show that the slower component is independent of the film thickness, while the faster one increases with the film thickness. Additionally, we could show that the diffusion behavior of the particles cannot be sufficiently described by only two diffusion coefficients.

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Trenkmann, Ines, Jörg Schuster, Shubhra Gangopadhyay, and Christian von Borczyskowski. "Investigation of solid liquid interface in ultra-thin liquid films via single particle tracking of colloidal particles." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-191812.

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Trenkmann, Ines, Daniela Täuber, Michael Bauer, Jörg Schuster, Sangho Bok, Shubhra Gangopadhyay, and Christian von Borczyskowski. "Investigations of solid liquid interfaces in ultra-thin liquid films via single particle tracking of silica particles." Diffusion fundamentals 11 (2009) 108, S. 1-12, 2009. https://ul.qucosa.de/id/qucosa%3A14082.

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Trenkmann, Ines, Jörg Schuster, Shubhra Gangopadhyay, and Christian von Borczyskowski. "Investigation of solid liquid interface in ultra-thin liquid films via single particle tracking of colloidal particles." Diffusion fundamentals 11 (2009) 115, S. 1-2, 2009. https://ul.qucosa.de/id/qucosa%3A14089.

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Heidernätsch, Mario, Michael Bauer, Daniela Täuber, Günter Radons, and Christian von Borcyskowski. "An advanced method of tracking temporarily invisible particles in video imaging." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-191774.

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Heidernätsch, Mario, Michael Bauer, Daniela Täuber, Günter Radons, and Christian von Borcyskowski. "An advanced method of tracking temporarily invisible particles in video imaging." Diffusion fundamentals 11 (2009) 111, S. 1-2, 2009. https://ul.qucosa.de/id/qucosa%3A14085.

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Книги з теми "Particles tracking"

library, Wiley online, ed. Single particle tracking and single molecule energy transfer. Weinheim: Wiley-VCH, 2010.

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United States. National Aeronautics and Space Administration., ed. Fuzzy logic particle tracking velocimetry. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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United States. National Aeronautics and Space Administration., ed. Particle displacement tracking for PIV. [Washington, DC]: National Aeronautics and Space Administration, 1990.

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M, Bright Michelle, Skoch Gary J, and NASA Glenn Research Center, eds. An investigation of surge in a high-speed centrifugal compressor using digital PIV. Cleveland, Ohio: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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United States. National Aeronautics and Space Administration., ed. Particle displacement tracking applied to air flows. [Washington, DC]: National Aeronautics and Space Administration, 1991.

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Ibrahim, Muhammad N. Application of tomographic techniques to particle tracking. Manchester: UMIST, 1997.

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Adam, Marion A. Mixing simulations based on particle tracking data. Manchester: UMIST, 1996.

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Stone, Lawrence D., Roy L. Streit, and Stephen L. Anderson. Introduction to Bayesian Tracking and Particle Filters. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32242-6.

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Figari, Rodolfo, and Alessandro Teta. Quantum Dynamics of a Particle in a Tracking Chamber. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40916-5.

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Frühwirth, Rudolf, and Are Strandlie. Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65771-0.

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Частини книг з теми "Particles tracking"

Metcalfe, Guy. "Tracking Particles in Tumbling Containers." In IUTAM Symposium on Mechanics of Granular and Porous Materials, 287–98. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5520-5_26.

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Chen, Huiying, and Youfu Li. "Optimized Particles for 3-D Tracking." In Intelligent Robotics and Applications, 749–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16584-9_71.

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Martinez, Brais, Marc Vivet, and Xavier Binefa. "Compatible Particles for Part-Based Tracking." In Articulated Motion and Deformable Objects, 1–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14061-7_1.

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Frühwirth, Rudolf, and Are Strandlie. "Secondary Vertex Reconstruction." In Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors, 159–65. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65771-0_9.

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AbstractThe chapter reviews methods for the search for secondary vertices. Four types of secondary vertices are discussed in detail: decays of short-lived particles, decays of long-lived particles, photon conversions, and hadronic interactions in the detector material.

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Salmond, David, and Neil Gordon. "Particles and Mixtures for Tracking and Guidance." In Sequential Monte Carlo Methods in Practice, 517–32. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3437-9_25.

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Gao, Tao, Zheng-guang Liu, and Jun Zhang. "Feature Particles Tracking for the Moving Object." In Studies in Computational Intelligence, 39–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92814-0_7.

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Zhu, Zhiren, and Jianfeng Wang. "Tracking of Fragmented Particles with Neural Networks." In Springer Series in Geomechanics and Geoengineering, 59–67. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-76528-5_6.

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D’Ambrosio, C., P. Destruel, U. Gensch, H. Güsten, H. Leutz, D. Puertolas, S. Schlenstedt, et al. "Scintillating Fibres for Central Tracking of Charged Particles." In New Technologies for Supercolliders, 173–84. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4684-1360-1_13.

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Babai, Mohammad, Nasser Kalantar-Nayestanaki, Johan G. Messchendorp, and Michael H. F. Wilkinson. "Tracking Sub-atomic Particles Through the Attribute Space." In Lecture Notes in Computer Science, 86–97. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18720-4_8.

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Biryukov, V., A. Drees, R. P. Fliller, N. Malitsky, and D. Trbojevic. "Tracking Particles In Accelerator Optics With Crystal Elements." In Lecture Notes in Computer Science, 372–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47789-6_39.

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Тези доповідей конференцій з теми "Particles tracking"

Grant, Patrick, Timo A. Nieminen, Alexander Stilgoe, and Halina Rubinsztein-Dunlop. "Tracking active matter particles with DeepTrack." In Emerging Topics in Artificial Intelligence (ETAI) 2024, edited by Giovanni Volpe, Joana B. Pereira, Daniel Brunner, and Aydogan Ozcan, 13. SPIE, 2024. http://dx.doi.org/10.1117/12.3027939.

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Mousavisani, Seyedmohammad, Scott D. Kelly, Sajad Kafashi, and Stuart T. Smith. "Particle Tracking Velocimetry in Noisy Environment." In ASME 2020 Fluids Engineering Division Summer Meeting collocated with the ASME 2020 Heat Transfer Summer Conference and the ASME 2020 18th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/fedsm2020-20401.

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Abstract The encoded Particle Tracking Velocimetry (ePTV) is introduce in this paper as a specific approach of Particle Tracking Velocimetry (PTV). This method is applied to track particles obtained from flow images that contain significant background noise and relatively low particle density. Encoding is achieved by illuminating the flow with a series of light pulses within individual image exposures. Dependent upon the velocity, each particle will be illuminated multiple times in each image frame with spacing determined by both the pulse train timing and the particle velocity. A search algorithm is used that identifies each particle and seeks the encoded pattern with other particles in the image, repeating this until all encoded particles are found. Based on probability analysis and finite image size an analytic model is developed to determine the ratio of true particles, false particles and those that are ‘lost’ by exiting the image frame. This ePTV technique has been experimentally implemented to track spherical particles suspended in stationary vortices. By using a suspension of micro-particles, subsequent imaging with encoded pulse trains provided snap-shots of the complex flow patterns. Typically, even after filtering, the images show around 100 to 200 particles from which encoded trajectories have been extracted and typically account for about 30% of the objects identified in the image.

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Guasto, Jeffrey S., Peter Huang, and Kenneth S. Breuer. "Statistical Particle Tracking Velocimetry Using Molecular and Quantum Dot Tracer Particles." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80051.

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We present the theory and experimental validation of a particle tracking velocimetry algorithm developed for application with nanometer-sized tracer particles such as fluorescent molecules and quantum dots (QDs). Traditional algorithms are challenged by extremely small tracers due to difficulties in determining the particle center, shot noise, high drop-in/drop-out and, in the case of quantum dots, fluorescence intermittency (blinking). The algorithms presented here determine real velocity distributions from measured particle displacement distributions by statistically removing randomly distributed tracking events. The theory was verified through tracking experiments using 54 nm flourescent dextran molecules and 6 nm QDs.

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Drake, Joshua B., Andrea L. Kenney, Timothy B. Morgan, and Theodore J. Heindel. "Developing Tracer Particles for X-Ray Particle Tracking Velocimetry." In ASME-JSME-KSME 2011 Joint Fluids Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajk2011-11009.

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X-ray imaging, as a noninvasive flow visualization technique, has been shown to be a useful method for observing and characterizing multiphase flows. One type of X-ray flow visualization technique, called X-ray Particle Tracking Velocimetry (XPTV), tracks an X-ray attenuating particle in an opaque fluid flow. A significant challenge with XPTV is identifying tracer particles with the desired fluid flow characteristics (e.g., small and neutrally buoyant) but yet differentially attenuate X-rays, which is based primarily on density differences. This paper describes the manufacturing of XPTV tracer particles that satisfy specific particle characteristics including high X-ray attenuation, uniform shape, specified effective density, and desired diameter. An example use of these particles as an intruder particle in a fluidized bed (to simulate biomass injection) is then demonstrated using X-ray stereographic imaging to determine intruder particle position as a function of time in a three-dimensional opaque system.

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Nazib, Abdullah, Chi-Min Oh, and Chil-Woo Lee. "Object tracking by supported particles." In 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2014. http://dx.doi.org/10.1109/urai.2014.7057484.

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Lin, Jian-Hung, and Keh-Chin Chang. "A Cost-Effective Search of Collision Pairs in Lagrangian Particle Tracking Method." In ASME/JSME/KSME 2015 Joint Fluids Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/ajkfluids2015-32577.

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In the simulation of particle-laden flows, in which the inter-particle collisions have to be considered, using the Eulerian-Lagrangian approach, it is agreed that the search of collision pairs based on the deterministic particle tracking method together with the binary-collision, hard-sphere model is a time consuming job in the computational procedure particularly for the flow laden with a remarkably high number density of particles. A cost-effective algorithm for the particle tracking processes which include solving the equations of motion, searching the collision pairs, and updating the list of neighboring particles’ indices is developed. It is demonstrated in the turbulent, fully developed, particle-laden channel flows that the computational expenditure required for completing the particle tracking processes in a given Lagrangian time step can be optimally made with an approximately linear proportionally to the total number of particles (NPT) by setting the number of Lagrangian cells (Ncell) for computation in accordance with the criterion of NPT / Ncell = O(10°).

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Zhong, Shengtong, and Fei Hao. "Hand Tracking by Particle Filtering with Elite Particles Mean Shift." In 2008 Japan-China Joint Workshop on Frontier of Computer Science and Technology (FCST). IEEE, 2008. http://dx.doi.org/10.1109/fcst.2008.9.

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Snoeyink, Craig A., Gordon Christopher, Sourav Barman, and Steve Wereley. "Sub-Diffraction Limit Three Dimensional Particle Tracking Velocimetry." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-65522.

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Here we present an optical measurement technique and image analysis process capable of tracking particles in three dimensions with a single point of view. In addition to single view 3D-PTV, the optical system is capable of tracking individual particles even at particle-particle spacings that are closer then the diffraction limit of the base imaging system. The measurement system, termed Bessel Beam Microscopy (BBM), functions as an attachment for a microscope that fits between the microscope base and camera. The addition of the BBM attachment transforms the point spread function (PSF) of the microscope allowing two unique functions: single image superresolution imaging, and the extraction of three dimension location information of particles without calibration. The result is a fluid characterization tool with unique capabilities for velocimetry and characterization of the dynamics of dense fluid-particle suspensions.

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Lessard, Guillaume A., Peter M. Goodwin, and James H. Werner. "Three-dimensional tracking of fluorescent particles." In Biomedical Optics 2006, edited by Jörg Enderlein and Zygmunt K. Gryczynski. SPIE, 2006. http://dx.doi.org/10.1117/12.650191.

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Yonggang Jin and F. Mokhtarian. "Towards robust head tracking by particles." In rnational Conference on Image Processing. IEEE, 2005. http://dx.doi.org/10.1109/icip.2005.1530529.

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Звіти організацій з теми "Particles tracking"

Trahan, Corey, Jing-Ru Cheng, and Amanda Hines. ERDC-PT : a multidimensional particle tracking model. Engineer Research and Development Center (U.S.), January 2023. http://dx.doi.org/10.21079/11681/48057.

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This report describes the technical engine details of the particle- and species-tracking software ERDC-PT. The development of ERDC-PT leveraged a legacy ERDC tracking model, “PT123,” developed by a civil works basic research project titled “Efficient Resolution of Complex Transport Phenomena Using Eulerian-Lagrangian Techniques” and in part by the System-Wide Water Resources Program. Given hydrodynamic velocities, ERDC-PT can track thousands of massless particles on 2D and 3D unstructured or converted structured meshes through distributed processing. At the time of this report, ERDC-PT supports triangular elements in 2D and tetrahedral elements in 3D. First-, second-, and fourth-order Runge-Kutta time integration methods are included in ERDC-PT to solve the ordinary differential equations describing the motion of particles. An element-by-element tracking algorithm is used for efficient particle tracking over the mesh. ERDC-PT tracks particles along the closed and free surface boundaries by velocity projection and stops tracking when a particle encounters the open boundary. In addition to passive particles, ERDC-PT can transport behavioral species, such as oyster larvae. This report is the first report of the series describing the technical details of the tracking engine. It details the governing equation and numerical approaching associated with ERDC-PT Version 1.0 contents.

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sun, yipeng. A Linac Simulation Code for Macro-Particles Tracking and Steering Algorithm Implementation. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1039538.

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Sun, Yipeng. A Linac Simulation Code for Macro-particles Tracking and Steering Algorithm Implementation. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1046379.

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Zhelyeznyakov, Maksym. Lagrangian particle tracking applied to high-speed tomographic particle imaging velocimetry. Office of Scientific and Technical Information (OSTI), August 2016. http://dx.doi.org/10.2172/1464440.

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O'Brien, M. Material Interface Reconstruction for Monte Carlo Particle Tracking. Office of Scientific and Technical Information (OSTI), March 2006. http://dx.doi.org/10.2172/895426.

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Mestha, L. K. Particle tracking code of simulating global RF feedback. Office of Scientific and Technical Information (OSTI), September 1991. http://dx.doi.org/10.2172/5986588.

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B. Robinson. Particle Tracking Model and Abstraction of Transport Processes. Office of Scientific and Technical Information (OSTI), April 2000. http://dx.doi.org/10.2172/837080.

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B. Robinson. Particle Tracking Model and Abstraction of Transport Processes. Office of Scientific and Technical Information (OSTI), October 2004. http://dx.doi.org/10.2172/839526.

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Liu, Xinmin, Zongli Lin, and Scott Acton. A New Particle Filter Based Algorithm for Image Tracking. Fort Belvoir, VA: Defense Technical Information Center, July 2008. http://dx.doi.org/10.21236/ada501159.

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Claus, J. A Different Approach to Non-Linearities and Particle Tracking. Office of Scientific and Technical Information (OSTI), October 1985. http://dx.doi.org/10.2172/1119268.

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