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Статті в журналах з теми "Tracking 2D"

Автор: Grafiati

Опубліковано: 24 липня 2022

Оновлено: 8 серпня 2022

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1

Kowalczyk, Anne, Claude Oelschlaeger, and Norbert Willenbacher. "Tracking errors in 2D multiple particle tracking microrheology." Measurement Science and Technology 26, no. 1 (December 1, 2014): 015302. http://dx.doi.org/10.1088/0957-0233/26/1/015302.

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2

Trache, Tudor, Stephan Stöbe, Adrienn Tarr, Dietrich Pfeiffer, and Andreas Hagendorff. "The agreement between 3D, standard 2D and triplane 2D speckle tracking: effects of image quality and 3D volume rate." Echo Research and Practice 1, no. 2 (November 2014): 71–83. http://dx.doi.org/10.1530/erp-14-0025.

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Анотація:

Comparison of 3D and 2D speckle tracking performed on standard 2D and triplane 2D datasets of normal and pathological left ventricular (LV) wall-motion patterns with a focus on the effect that 3D volume rate (3DVR), image quality and tracking artifacts have on the agreement between 2D and 3D speckle tracking. 37 patients with normal LV function and 18 patients with ischaemic wall-motion abnormalities underwent 2D and 3D echocardiography, followed by offline speckle tracking measurements. The values of 3D global, regional and segmental strain were compared with the standard 2D and triplane 2D strain values. Correlation analysis with the LV ejection fraction (LVEF) was also performed. The 3D and 2D global strain values correlated good in both normally and abnormally contracting hearts, though systematic differences between the two methods were observed. Of the 3D strain parameters, the area strain showed the best correlation with the LVEF. The numerical agreement of 3D and 2D analyses varied significantly with the volume rate and image quality of the 3D datasets. The highest correlation between 2D and 3D peak systolic strain values was found between 3D area and standard 2D longitudinal strain. Regional wall-motion abnormalities were similarly detected by 2D and 3D speckle tracking. 2DST of triplane datasets showed similar results to those of conventional 2D datasets. 2D and 3D speckle tracking similarly detect normal and pathological wall-motion patterns. Limited image quality has a significant impact on the agreement between 3D and 2D numerical strain values.

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3

Жерко, О. М., and Э. И. Шкребнева. "2D Speckle Tracking Echocardiography in Predicting Diastolic Right Ventricular Dysfunction." Кардиология в Беларуси, no. 5 (January 5, 2021): 679–87. http://dx.doi.org/10.34883/pi.2020.12.5.006.

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Цель. Разработать прогностические критерии диастолической дисфункции (ДД) правого желудочка (ПЖ) по данным 2D Speckle Tracking эхокардиографии (STE).Материалы и методы. В 2019 г. на базе ГУ «Минский научно-практический центр хирургии, трансплантологии и гематологии» выполнено клинико-инструментальное исследование 91 пациента в возрасте 64,0 [58,0; 70,0] года. Критерии включения в исследование: синусовый ритм, эссенциальная артериальная гипертензия, хроническая ишемическая болезнь сердца, перенесенный в прошлом инфаркт миокарда ЛЖ, после которого прошло не менее полугода для стабилизации структурно-функциональных показателей ЛЖ, хроническая сердечная недостаточность. Критерии исключения: первичная митральная регургитация, митральный стеноз, пластика или протезирование митрального клапана, врожденные пороки сердца, острые и хронические заболевания почек, легких. Трансторакальная эхокардиография и STE выполнялись на ультразвуковом аппарате Vivid E9 (GE Healthcare, США).Результаты. Ведущими функциональными аномалиями, взаимосвязанными c ДД ПЖ, при сохраненной сократимости ПЖ и нормальном систолическом давлении в ПЖ, являются снижение продольных диастолических, регионарных и глобальной систолических деформаций ПЖ, механическая дисперсия миокарда ПЖ: установлены статистически значимые взаимосвязи между ДД и величинами ранней диастолической продольной деформации Е базальносептального сегмента (r=0,63, p<0,001), базальнолатерального сегмента ПЖ (r=0,61, p<0,001), отношением ранних и поздних диастолических продольных деформаций Е/А базальнолатерального сегмента ПЖ (r=–0,66, p<0,001), глобальным постсистолическим индексом ПЖ (r=0,45, p=0,0002), индексом раннего систолического растяжения боковой стенки ПЖ (r=0,41, p<0,001), индексом механической дисперсии ПЖ (r=0,31, p=0,003), глобальной продольной систолической деформацией ПЖ (GLS) (r=0,61, p<0,001). Прогностические для ДД ПЖ значения ранней диастолической деформации Е базальносептального сегмента ПЖ составляют >–5,66% (чувствительность 76,9%, специфичность 85,7%), базальнолатерального сегмента ПЖ >–8,74% (чувствительность 91,1%, специфичность 70,8%), отношение ранней и поздней диастолических продольных деформаций Е/А базальнолатерального сегмента ПЖ ≤0,67(чувствительность 62,2%, специфичность 100,0%), значение GLS ПЖ >–19,8% (чувствитель-ность 63,8%, специфичность 93,1%).Выводы. Применение в практическом здравоохранении разработанных прогностических показателей STE позволит повысить эффективность диагностики ДД ПЖ. Purpose. To develop the prognostic criteria of diastolic dysfunction (DD) of the right ventricle (RV), according to speckle tracking echocardiography (STE).Materials and methods. A clinical and instrumental study of 91 patients aged 64.0 [58.0; 70.0] years was performed on base of the State Institution “Minsk Scientific and Practical Center of Surgery, Transplantology and Hematology” in 2019. The criteria for inclusion in the study were the following: sinus rhythm, essential arterial hypertension, chronic coronary heart disease, previous left myocardial infarction, after which at least six months have passed to stabilize the structural and functional parameters of the left ventricle, chronic heart failure. Exclusion criteria were the following: primary mitral regurgitation, mitral stenosis, mitral valve repair or prosthetics, congenital heart defects, acute and chronic diseases of the kidneys, lungs. Transthoracic echocardiography and STE were performed on the ultrasound machine Vivid E9 (GE Healthcare, USA).Results. The leading functional anomalies that are interconnected with RV DD, with saved RV contractility and RV systolic pressure, are the decrease of RV longitudinal diastolic, regional and global systolic strain, RV mechanical dispersion: statistically significant relationships were revealed between DD and the values of early diastolic longitudinal strain E of the RV basal-septal segment (r=0.63, p<0.001), the RV basal-lateral segment (r=0.61, p <0.001), the ratio of early and late diastolic longitudinal deformations E/A of the RV basal lateral segment (r=–0.66, p<0.001), the global post- systolic index (r=0.45, p=0.0002), the pre-stretch index of the RV lateral wall (r=0.41, p<0.001), RV mechanical dispersion index (r=0.31, p=0.003), RV global longitudinal systolic deformation (GLS) (r=0.61, p<0.001). The values of early diastolic deformation E of the RV basal-septal segment, prognostic for RV DD, are >–5.66% (sensitivity 76.9%, specificity 85.7%), RV basal-lateral segment>–8.74% (sensitivity 91.1%, specificity 70.8%), the ratio of early and late diastolic longitudinal deformations E/A of the RV basal lateral segment ≤0.67 (sensitivity 62.2%, specificity 100.0%), RV GLS >–19.8% (sensitivity 63.8%, specificity 93.1%).Conclusion. The use of the developed STE prognostic indicators in RV DD will increase the efficiency of diagnosis of RV DD.

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4

Masutani, Satoshi. "Let’s Start Speckle Tracking Echocardiography." Pediatric Cardiology and Cardiac Surgery 32, no. 2 (2016): 78–86. http://dx.doi.org/10.9794/jspccs.32.78.

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5

Montagnini, Anna, Miriam Spering, and Guillaume S. Masson. "Predicting 2D Target Velocity Cannot Help 2D Motion Integration for Smooth Pursuit Initiation." Journal of Neurophysiology 96, no. 6 (December 2006): 3545–50. http://dx.doi.org/10.1152/jn.00563.2006.

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Анотація:

Smooth pursuit eye movements reflect the temporal dynamics of bidimensional (2D) visual motion integration. When tracking a single, tilted line, initial pursuit direction is biased toward unidimensional (1D) edge motion signals, which are orthogonal to the line orientation. Over 200 ms, tracking direction is slowly corrected to finally match the 2D object motion during steady-state pursuit. We now show that repetition of line orientation and/or motion direction does not eliminate the transient tracking direction error nor change the time course of pursuit correction. Nonetheless, multiple successive presentations of a single orientation/direction condition elicit robust anticipatory pursuit eye movements that always go in the 2D object motion direction not the 1D edge motion direction. These results demonstrate that predictive signals about target motion cannot be used for an efficient integration of ambiguous velocity signals at pursuit initiation.

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6

Ham, Dahye, Hyung-Chan Cho, Yoo-Jung Yoon, Won-Sang Ra, and Seul-Ki Han. "Feature Based Extended Target Tracking Using Automotive 2D LIDAR." Transactions of The Korean Institute of Electrical Engineers 70, no. 1 (January 31, 2021): 224–35. http://dx.doi.org/10.5370/kiee.2021.70.1.224.

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7

Ho, Hsin-Yang, I.-Cheng Yeh, Yu-Chi Lai, Wen-Chieh Lin, and Fu-Yin Cherng. "Evaluating 2D Flow Visualization Using Eye Tracking." Computer Graphics Forum 34, no. 3 (June 2015): 501–10. http://dx.doi.org/10.1111/cgf.12662.

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8

Oussalah, Mourad, and Joris De Schutter. "Possibilistic Kalman filtering for radar 2D tracking." Information Sciences 130, no. 1-4 (December 2000): 85–107. http://dx.doi.org/10.1016/s0020-0255(00)00076-1.

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9

Benhimane, S., and E. Malis. "Homography-based 2D Visual Tracking and Servoing." International Journal of Robotics Research 26, no. 7 (July 2007): 661–76. http://dx.doi.org/10.1177/0278364907080252.

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10

Krishnan, Srivatsan, and Daniel Raviv. "2D feature tracking algorithm for motion analysis." Pattern Recognition 28, no. 8 (August 1995): 1103–26. http://dx.doi.org/10.1016/0031-3203(95)00006-l.

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11

Chen, Kai-Yu, Li-Wei Chou, Hui-Min Lee, Shuenn-Tsong Young, Cheng-Hung Lin, Yi-Shu Zhou, Shih-Tsang Tang, and Ying-Hui Lai. "Human Motion Tracking Using 3D Image Features with a Long Short-Term Memory Mechanism Model—An Example of Forward Reaching." Sensors 22, no. 1 (December 31, 2021): 292. http://dx.doi.org/10.3390/s22010292.

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Human motion tracking is widely applied to rehabilitation tasks, and inertial measurement unit (IMU) sensors are a well-known approach for recording motion behavior. IMU sensors can provide accurate information regarding three-dimensional (3D) human motion. However, IMU sensors must be attached to the body, which can be inconvenient or uncomfortable for users. To alleviate this issue, a visual-based tracking system from two-dimensional (2D) RGB images has been studied extensively in recent years and proven to have a suitable performance for human motion tracking. However, the 2D image system has its limitations. Specifically, human motion consists of spatial changes, and the 3D motion features predicted from the 2D images have limitations. In this study, we propose a deep learning (DL) human motion tracking technology using 3D image features with a deep bidirectional long short-term memory (DBLSTM) mechanism model. The experimental results show that, compared with the traditional 2D image system, the proposed system provides improved human motion tracking ability with RMSE in acceleration less than 0.5 (m/s2) X, Y, and Z directions. These findings suggest that the proposed model is a viable approach for future human motion tracking applications.

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12

Gill, Gobind S., Brady Hunt, Rongxiao Zhang, Benjamin B. Williams, Charles R. Thomas, and Bassem I. Zaki. "Initial observation of contrast profiles for 3D and 2D MRI sequences in MR-guided radiation therapy for locally advanced pancreatic cancer." Journal of Clinical Oncology 40, no. 4_suppl (February 1, 2022): 541. http://dx.doi.org/10.1200/jco.2022.40.4_suppl.541.

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541 Background: MR-guided stereotactic body radiation therapy (MR-SBRT) is a novel method of treating mobile tumors with soft-tissue gating and on-table adaptive planning. In our experience using the ViewRay MRIdian system (VR) for treating locally advanced pancreatic cancer (PA) with MR-SBRT, the true-fast imaging with steady-state free precession (TRUFI) sequences on the VR impart differing intensities for relevant structures seen on the pre-treatment high resolution 3D MRI (3D MRI) versus the real-time 2D cine MRI (2D cine) used for target tracking. Since these variations can confound target tracking selection, we propose that an understanding of the differing contrast profiles could improve selection of tracking structures and optimize treatment delivery. Methods: We retrospectively reviewed both 3D MRI and 2D cine images for patients (pts) with PA (n =20) treated on the VR. At simulation, an appropriate tracking target was identified and contoured on a single 3mm sagittal slice of the 3D MRI. This sagittal slice was directly compared to the registered 7mm 2D cine to identify structures with notable discrepancies in signal intensity. The 3D MRI was then explored in additional planes to confirm structure identities. For quantitative verification of the clinically observed differences, the pixel intensity distributions of 3D MRI and 2D cine DICOM image datasets were statistically compared. Results: In all pts reviewed, arteries (aorta, celiac, SMA) appeared with similar contrast profiles on both images. However, veins (portal vein, SMV) appeared hypointense on 3D MRI but hyperintense on 2D cine. Biliary structures appeared hyperintense on 3D MRI but only mildly hyperintense on 2D cine. The pixel intensity distributions extracted from 3D MRI and 2D cine images were confirmed to differ significantly (two sample Kolmogorov-Smirnov test; test statistic =0.40; p < 0.001). Conclusions: There are significant variations in image intensity between the initial treatment planning 3D MRI and the immediate pre-treatment 2D cine obtained with the VR. Understanding these discrepancies can guide radiation oncologists in choosing optimal tracking targets. Future work will focus on identifying the particular causes and frequencies of target tracking failures and exploring alternative tracking algorithms using artificial intelligence which could ultimately allow for VMAT on the ViewRay system.

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13

Alexander, Amy L., and Christopher D. Wickens. "Flightpath Tracking, Change Detection and Visual Scanning in an Integrated Hazard Display." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 1 (September 2005): 68–72. http://dx.doi.org/10.1177/154193120504900116.

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Twenty-four certified flight instructors were required to fly a series of curved, step-down approaches while detecting changes to surrounding traffic aircraft and weather cell icons on two integrated hazard display (IHD) formats (2D coplanar and split-screen) under varying workload levels. Generally, it appears that the 2D coplanar IHD was better in supporting flightpath tracking and change detection performance when compared to a split-screen display. Pilots exhibited superior flightpath tracking (in the vertical dimension, and under low workload) when using the 2D coplanar IHD, although this effect was mitigated by increasing workload such that tracking deteriorated faster with the 2D coplanar than the split-screen display. The spawned 3D cost of diminished size with distance from ownship played a role in change detection response time—pilots were slower (particularly in detecting traffic aircraft changes) with the split-screen compared to the 2D coplanar IHD. These effects will be discussed within the context of visual scanning measures.

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14

Tan, Qingwen, and Seung-Soo Baek. "Analysis and Research on the Timeliness of Virtual Reality Sports Actions in Football Scenes." Wireless Communications and Mobile Computing 2021 (November 19, 2021): 1–9. http://dx.doi.org/10.1155/2021/8687378.

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In the complex and changing situation on the soccer field, players must always be aware of their teammates, opponents, and the position of the ball during the game, constantly updating and analyzing the strategic information of the opponent in order to make appropriate tactical decisions. This ability to track multiple objects at the same time is also a prerequisite for high-level soccer players to be able to react quickly and appropriately during the game. Therefore, it is essential to examine the attentional ability of soccer players in dynamic scenarios. This study compares soccer players’ performance in 2D planar and 3D virtual reality dynamic tracking tasks in two dimensions. They are correct tracking rate and tracking speed. This paper examines the tracking performance and spatial attention allocation characteristics of soccer players in different dynamic tracking tasks and the differences with the average college students by manipulating different types of 2D dynamic tracking tasks and incorporating a point detection paradigm. It was found that there were no differences in correct tracking and detection stimulus awareness between soccer players and college students in different 2D dynamic tracking tasks, showing consistency across populations. In terms of correct tracking rates, both soccer players and university students showed the highest correct tracking rates in the location MIT task, followed by the MOT task, and the worst in the identity MIT task. This indicates that the good dynamic attention ability of soccer players was not reflected in the above 2D dynamic tracking process. However, soccer players and college students showed consistent characteristics across populations in different dynamic tracking tasks. The results of detection stimulus awareness showed that soccer players and college students had the same trend of attention allocation between dynamic tracking tasks, i.e., more attention to the blank area of the screen and the target object and less attention to the distractor. This suggests that there was a distractor suppression effect between different dynamic tracking tasks.

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15

Yoon, Jong-Hyun, and Jong-Seung Park. "Robust 2D Feature Tracking in Long Video Sequences." KIPS Transactions:PartB 14B, no. 7 (December 31, 2007): 473–80. http://dx.doi.org/10.3745/kipstb.2007.14-b.7.473.

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16

Casado, Fernando, Yago Luis lapido, Diego P. Losada, and Alejandro Santana-Alonso. "Pose Estimation and Object Tracking Using 2D Images." Procedia Manufacturing 11 (2017): 63–71. http://dx.doi.org/10.1016/j.promfg.2017.07.134.

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17

Jang, Dae-Sik, Seok-Woo Jang, and Hyung-Il Choi. "2D human body tracking with Structural Kalman filter." Pattern Recognition 35, no. 10 (October 2002): 2041–49. http://dx.doi.org/10.1016/s0031-3203(01)00201-1.

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18

Polat, Ediz, Mohammed Yeasin, and Rajeev Sharma. "A 2D/3D model-based object tracking framework." Pattern Recognition 36, no. 9 (September 2003): 2127–41. http://dx.doi.org/10.1016/s0031-3203(03)00041-4.

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19

Bernardino, Alexandre, José Santos-Victor, and Giulio Sandini. "Foveated active tracking with redundant 2D motion parameters." Robotics and Autonomous Systems 39, no. 3-4 (June 2002): 205–21. http://dx.doi.org/10.1016/s0921-8890(02)00205-1.

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20

Yoo, Haanju, Hyeun Jun Moon, Seung-Hoon Kim, and Sang-Il Choi. "Multi-Target Tracking With Multiple 2D Range Scanners." IEEE Access 8 (2020): 99990–98. http://dx.doi.org/10.1109/access.2019.2893485.

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21

Liubartseva, S., G. Coppini, R. Lecci, and E. Clementi. "Tracking plastics in the Mediterranean: 2D Lagrangian model." Marine Pollution Bulletin 129, no. 1 (April 2018): 151–62. http://dx.doi.org/10.1016/j.marpolbul.2018.02.019.

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22

Xiao, Bo, Ruiqi Chen, and Zhenhua Zhu. "2D Part-Based Visual Tracking of Hydraulic Excavators." World Journal of Engineering and Technology 04, no. 03 (2016): 101–11. http://dx.doi.org/10.4236/wjet.2016.43c013.

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23

Pak, Jung Min. "Gaussian Sum FIR Filtering for 2D Target Tracking." International Journal of Control, Automation and Systems 18, no. 3 (September 23, 2019): 643–49. http://dx.doi.org/10.1007/s12555-018-0938-4.

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24

Lou, Zhongyu, Guang Jiang, and Chengke Wu. "2D scale-adaptive tracking based on projective geometry." Multimedia Tools and Applications 72, no. 1 (March 8, 2013): 905–24. http://dx.doi.org/10.1007/s11042-013-1407-y.

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25

Acres, Jacqueline, and Jay Nadeau. "2D vs 3D tracking in bacterial motility analysis." AIMS Biophysics 8, no. 4 (2021): 385–99. http://dx.doi.org/10.3934/biophy.2021030.

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<abstract> <p>Digital holographic microscopy provides the ability to observe throughout a large volume without refocusing. This capability enables simultaneous observations of large numbers of microorganisms swimming in an essentially unconstrained fashion. However, computational tools for tracking large 4D datasets remain lacking. In this paper, we examine the errors introduced by tracking bacterial motion as 2D projections vs. 3D volumes under different circumstances: bacteria free in liquid media and bacteria near a glass surface. We find that while XYZ speeds are generally equal to or larger than XY speeds, they are still within empirical uncertainties. Additionally, when studying dynamic surface behavior, the Z coordinate cannot be neglected.</p> </abstract>

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26

Ciallella, Mirco, Mario Ricchiuto, Renato Paciorri, and Aldo Bonfiglioli. "Extrapolated DIscontinuity Tracking for complex 2D shock interactions." Computer Methods in Applied Mechanics and Engineering 391 (March 2022): 114543. http://dx.doi.org/10.1016/j.cma.2021.114543.

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27

Mohedano, Raul, and Narciso Garcia. "Robust multi-camera 3D tracking from mono-camera 2d tracking using Bayesian Association." IEEE Transactions on Consumer Electronics 56, no. 1 (February 2010): 1–8. http://dx.doi.org/10.1109/tce.2010.5439118.

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28

Wallace, Julian M., Leland S. Stone, and Guillaume S. Masson. "Object Motion Computation for the Initiation of Smooth Pursuit Eye Movements in Humans." Journal of Neurophysiology 93, no. 4 (April 2005): 2279–93. http://dx.doi.org/10.1152/jn.01042.2004.

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Pursuing an object with smooth eye movements requires an accurate estimate of its two-dimensional (2D) trajectory. This 2D motion computation requires that different local motion measurements are extracted and combined to recover the global object-motion direction and speed. Several combination rules have been proposed such as vector averaging (VA), intersection of constraints (IOC), or 2D feature tracking (2DFT). To examine this computation, we investigated the time course of smooth pursuit eye movements driven by simple objects of different shapes. For type II diamond (where the direction of true object motion is dramatically different from the vector average of the 1-dimensional edge motions, i.e., VA ≠ IOC = 2DFT), the ocular tracking is initiated in the vector average direction. Over a period of less than 300 ms, the eye-tracking direction converges on the true object motion. The reduction of the tracking error starts before the closing of the oculomotor loop. For type I diamonds (where the direction of true object motion is identical to the vector average direction, i.e., VA = IOC = 2DFT), there is no such bias. We quantified this effect by calculating the direction error between responses to types I and II and measuring its maximum value and time constant. At low contrast and high speeds, the initial bias in tracking direction is larger and takes longer to converge onto the actual object-motion direction. This effect is attenuated with the introduction of more 2D information to the extent that it was totally obliterated with a texture-filled type II diamond. These results suggest a flexible 2D computation for motion integration, which combines all available one-dimensional (edge) and 2D (feature) motion information to refine the estimate of object-motion direction over time.

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29

Ranjbar, Vahid H. "Effect of Overlapping Intrinsic Spin Resonances on e-Lens Lattices from FY13 Polarized Proton Run." International Journal of Modern Physics: Conference Series 40 (January 2016): 1660088. http://dx.doi.org/10.1142/s2010194516600880.

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During the 2013 Polarized Proton run RHIC was run with a lattice designed to accommodate the phases necessary for the Electron lens. This lattice resulted in significant changes in magnitude and distribution of the intrinsic resonances. The overall magnitude of the strong intrinsic resonances were smaller, however the neighbouring weak intrinsic resonances grew. We present results from 2D direct tracking with 5,000 particles and 2D lattice independent tracking .

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Licciardello, C., A. Di Marco, S. Biagini, D. Palazzuoli, and K. Tayeh. "2D/3D SOIL CONSUMPTION TRACKING IN A MARBLE QUARRY DISTRICT." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 5, 2022): 259–64. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-259-2022.

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Abstract. Complex extractive districts, such as the marble quarries in the Apuan Alps (northern Italy), require soil consumption monitoring over the years that could be achieved through high-resolution remotely sensed data. To derive 2D and 3D indicators with appropriate resolution for annual monitoring of high-resolution changes in soil consumption, aerial images, LiDAR acquisitions, satellite data, and Remotely Piloted Aircraft Systems (RPAS) acquisitions were used. In particular, open-access Sentinel-2 multispectral satellite imagery with a spatial resolution of 10 m was used to assess cover changes (2D), and then refined by manual interpretation for 5 years (2016-2021). 3D changes were detected by comparing free aerial LiDAR data from 2009 and 2017, integrated with two stereo models obtained from Pléiades high-resolution satellite images from 2020 and 2022. 3D changes observed over the years by algebraic elevation comparison, performed in QGIS 3.x environment, highlight quarries characterized by intense mining activities (extracted marble blocks, characterized by positive elevation differences) and quarry area management (debris disposal and service infrastructure construction, characterized by negative elevation differences). The combined use of 2D and 3D change indicators can be challenging in order to correctly represent soil consumption over the years. A dual 2D/3D webgis client have been developed for proper representation of 2D/3D spatial indicators of ongoing extraction activities in the Carrara marble basin: high-resolution images have been served as tiled data, while 2D/3D spatial indicators are served as static and/or tiled vector data. Open-Source libraries have used in data processing, serving and representation inside a map interface.

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31

Cui, Hao, Zhong Qiu Wang, Hui Liu, and Yan Xu. "Surf Crest Tracking Algorithm in Wave Image." Applied Mechanics and Materials 482 (December 2013): 341–45. http://dx.doi.org/10.4028/www.scientific.net/amm.482.341.

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The non-contact ocean wave observation based on shore station could be impacted on high accuracy of surf crest 2D coordinate in wave images. Focus on previous disadvantages such as lower speed and accuracy, a novel surf crest tracking algorithm is represented with crest collapse function which could terminate the tracking process through end point adjustment. The algorithm could not only process the concerned part of the wave image automatically with higher speed, but also record 2D coordinate of every point on the concerned surf crest and the connection between every two contiguous points accurately, which are very practicable in the non-contact ocean wave observation.

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32

Wu, Tao, Pengtao Zhang, Yiwen Li, Yangjun Gao, Chaoqi Fu, and Bo Feng. "DOA Tracking of Two-Dimensional Coherent Distribution Source Based on Fast Approximated Power Iteration." Mathematical Problems in Engineering 2020 (November 16, 2020): 1–12. http://dx.doi.org/10.1155/2020/3219516.

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Aiming at two-dimensional (2D) coherent distributed (CD) sources, this paper has proposed a direction of arrival (DOA) tracking algorithm based on signal subspace updating under the uniform rectangular array (URA). First, based on the hypothesis of small angular spreads of distributed sources, the rotating invariant relations of the signal subspace of the receive vector of URA are derived. An ESPRIT-like method is constructed for DOA estimation using two adjacent parallel linear arrays of URA. Through the synthesis of estimation by multiple groups of parallel linear arrays within URA arrays, the DOA estimation method for 2D CD sources based on URA is obtained. Then, fast approximated power iteration (FAPI) subspace tracking algorithm is used to update the signal subspace. In this way, DOA tracking of 2D CD sources can be realized by DOA estimation through signal subspace updating. This algorithm has a low computational complexity and good real-time tracking performance. In addition, the algorithm can track multiple CD sources without knowing the angular signal distribution functions, which is robust to model errors.

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33

Blakey, William Andrew, Stamos Katsigiannis, Navid Hajimirza, and Naeem Ramzan. "Defining gaze tracking metrics by observing a growing divide between 2D and 3D tracking." Electronic Imaging 2020, no. 11 (January 26, 2020): 129–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.11.hvei-129.

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This work examines the different terminology used for defining gaze tracking technology and explores the different methodologies used for describing their respective accuracy. Through a comparative study of different gaze tracking technologies, such as infrared and webcam-based, and utilising a variety of accuracy metrics, this work shows how the reported accuracy can be misleading. The lack of intersection points between the gaze vectors of different eyes (also known as convergence points) in definitions has a huge impact on accuracy measures and directly impacts the robustness of any accuracy measuring methodology. Different accuracy metrics and tracking definitions have been collected and tabulated to more formally demonstrate the divide in definitions.

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34

Cuculi, Florim, Michel Zuber, and Paul Erne. "Quantification by Speckle Tracking at Rest and During Stress." European Cardiology Review 6, no. 4 (2010): 16. http://dx.doi.org/10.15420/ecr.2010.6.4.16.

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The introduction of speckle tracking imaging and the opportunity to objectify regional myocardial function in an angle-independent fashion has opened a wide array of opportunities. Quantitative echocardiography is likely to reduce intra-observer variability and shorten learning curves and this will allow broader use of these new imaging modalities in clinical routine and for research purposes. Tissue Doppler is used for deformation imaging, but has disadvantages that can be overcome with 2D speckle tracking. This article briefly summarises the technical details of 2D speckle tracking (strain and strain rate) and gives an overview on current and potential future applications of this new technique at rest and during stress.

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35

Plášek, Jiří, Tomáš Rychlý, Diana Drieniková, Ondřej Cisovský, Tomáš Grézl, Miroslav Homza, and Jan Václavík. "The Agreement of a Two- and a Three-Dimensional Speckle-Tracking Global Longitudinal Strain." Journal of Clinical Medicine 11, no. 9 (April 25, 2022): 2402. http://dx.doi.org/10.3390/jcm11092402.

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Background: Two-dimensional (2D) and three-dimensional (3D) speckle-tracking echocardiography (STE) enables assessment of myocardial function. Here, we examined the agreement between 2D and 3D STE measurement of a global longitudinal strain (GLS) in patients with normal left ventricle, reduced ejection fraction, and cardiac pacing. Methods: Our analysis included 90 consecutive patients (59% males; average age: 73.2 ± 11.2 years) examined between May 2019–December 2020, with valid 2D and 3D loops for further speckle-tracking strain analysis. Linear regression, Pearson correlation, and a Bland–Altman plot were used to quantify the association between 2D and 3D GLS and related segments, using the 17-segment American Heart Association (AHA) model. Analyses were performed in the entire study group and subgroups. Intra- and inter-observer variability of 2D and 3D GLS measurement was also performed in all participants. Results: We observed a strong correlation between 2D and 3D GLS measurements (R = 0.76, p < 0.001), which was higher in males (R = 0.78, p < 0.001) than females (R = 0.69, p < 0.001). Associated segment correlation was poor (R = 0.2–0.5, p < 0.01). The correlation between 2D and 3D GLS was weaker in individuals with ventricular pacing of >50% (R = 0.62, p < 0.001) than <50% (R = 0.8, p < 0.001), and in patients with LVEF of <35% (R = 0.69, p = 0.002) than >35% (R = 0.72, p < 0.001). Intra-observer variability for 2D and 3D GLS was 2 and 2.3%, respectively. Inter-observer variability for 2D and 3D GLS was 3.8 and 3.6%, respectively Conclusion: Overall 2D and 3D GLS were closely associated but not when analyzed per segment. It seems that GLS comparison is more representative of global shortening than local displacement. Right ventricular pacing and reduced left ventricular ejection fraction were associated with a reduced correlation between 2D and 3D GLS.

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36

Plášek, Jiří, Tomáš Rychlý, Diana Drieniková, Ondřej Cisovský, Tomáš Grézl, Miroslav Homza, and Jan Václavík. "The Agreement of a Two- and a Three-Dimensional Speckle-Tracking Global Longitudinal Strain." Journal of Clinical Medicine 11, no. 9 (April 25, 2022): 2402. http://dx.doi.org/10.3390/jcm11092402.

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Анотація:

Background: Two-dimensional (2D) and three-dimensional (3D) speckle-tracking echocardiography (STE) enables assessment of myocardial function. Here, we examined the agreement between 2D and 3D STE measurement of a global longitudinal strain (GLS) in patients with normal left ventricle, reduced ejection fraction, and cardiac pacing. Methods: Our analysis included 90 consecutive patients (59% males; average age: 73.2 ± 11.2 years) examined between May 2019–December 2020, with valid 2D and 3D loops for further speckle-tracking strain analysis. Linear regression, Pearson correlation, and a Bland–Altman plot were used to quantify the association between 2D and 3D GLS and related segments, using the 17-segment American Heart Association (AHA) model. Analyses were performed in the entire study group and subgroups. Intra- and inter-observer variability of 2D and 3D GLS measurement was also performed in all participants. Results: We observed a strong correlation between 2D and 3D GLS measurements (R = 0.76, p < 0.001), which was higher in males (R = 0.78, p < 0.001) than females (R = 0.69, p < 0.001). Associated segment correlation was poor (R = 0.2–0.5, p < 0.01). The correlation between 2D and 3D GLS was weaker in individuals with ventricular pacing of >50% (R = 0.62, p < 0.001) than <50% (R = 0.8, p < 0.001), and in patients with LVEF of <35% (R = 0.69, p = 0.002) than >35% (R = 0.72, p < 0.001). Intra-observer variability for 2D and 3D GLS was 2 and 2.3%, respectively. Inter-observer variability for 2D and 3D GLS was 3.8 and 3.6%, respectively Conclusion: Overall 2D and 3D GLS were closely associated but not when analyzed per segment. It seems that GLS comparison is more representative of global shortening than local displacement. Right ventricular pacing and reduced left ventricular ejection fraction were associated with a reduced correlation between 2D and 3D GLS.

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37

Plášek, Jiří, Tomáš Rychlý, Diana Drieniková, Ondřej Cisovský, Tomáš Grézl, Miroslav Homza, and Jan Václavík. "The Agreement of a Two- and a Three-Dimensional Speckle-Tracking Global Longitudinal Strain." Journal of Clinical Medicine 11, no. 9 (April 25, 2022): 2402. http://dx.doi.org/10.3390/jcm11092402.

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Анотація:

Background: Two-dimensional (2D) and three-dimensional (3D) speckle-tracking echocardiography (STE) enables assessment of myocardial function. Here, we examined the agreement between 2D and 3D STE measurement of a global longitudinal strain (GLS) in patients with normal left ventricle, reduced ejection fraction, and cardiac pacing. Methods: Our analysis included 90 consecutive patients (59% males; average age: 73.2 ± 11.2 years) examined between May 2019–December 2020, with valid 2D and 3D loops for further speckle-tracking strain analysis. Linear regression, Pearson correlation, and a Bland–Altman plot were used to quantify the association between 2D and 3D GLS and related segments, using the 17-segment American Heart Association (AHA) model. Analyses were performed in the entire study group and subgroups. Intra- and inter-observer variability of 2D and 3D GLS measurement was also performed in all participants. Results: We observed a strong correlation between 2D and 3D GLS measurements (R = 0.76, p < 0.001), which was higher in males (R = 0.78, p < 0.001) than females (R = 0.69, p < 0.001). Associated segment correlation was poor (R = 0.2–0.5, p < 0.01). The correlation between 2D and 3D GLS was weaker in individuals with ventricular pacing of >50% (R = 0.62, p < 0.001) than <50% (R = 0.8, p < 0.001), and in patients with LVEF of <35% (R = 0.69, p = 0.002) than >35% (R = 0.72, p < 0.001). Intra-observer variability for 2D and 3D GLS was 2 and 2.3%, respectively. Inter-observer variability for 2D and 3D GLS was 3.8 and 3.6%, respectively Conclusion: Overall 2D and 3D GLS were closely associated but not when analyzed per segment. It seems that GLS comparison is more representative of global shortening than local displacement. Right ventricular pacing and reduced left ventricular ejection fraction were associated with a reduced correlation between 2D and 3D GLS.

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38

Chen, Zihong, Lingxiang Zheng, Yuqi Chen, and Yixiong Zhang. "2D Hand Tracking Based on Flocking with Obstacle Avoidance." International Journal of Advanced Robotic Systems 11, no. 2 (January 2014): 22. http://dx.doi.org/10.5772/57450.

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39

Tian, Jinglan, Ling Li, and Wanquan Liu. "Multi-Scale Human Pose Tracking in 2D Monocular Images." Journal of Computer and Communications 02, no. 02 (2014): 78–84. http://dx.doi.org/10.4236/jcc.2014.22014.

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40

Oh, Chi-Min, Mun-Ho Jeong, Bum-Jae You, and Chil-Woo Lee. "2D Planar Object Tracking using Improved Chamfer Matching Likelihood." KIPS Transactions:PartB 17B, no. 1 (February 28, 2010): 37–46. http://dx.doi.org/10.3745/kipstb.2010.17b.1.037.

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41

Albinsson, John, Hideyuki Hasegawa, Hiroki Takahashi, Enrico Boni, Alessandro Ramalli, Åsa Rydén Ahlgren, and Magnus Cinthio. "Iterative 2D Tissue Motion Tracking in Ultrafast Ultrasound Imaging." Applied Sciences 8, no. 5 (April 25, 2018): 662. http://dx.doi.org/10.3390/app8050662.

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42

Abe, Y., and J. Popovic. "Simulating 2D Gaits with a Phase-Indexed Tracking Controller." IEEE Computer Graphics and Applications 31, no. 4 (July 2011): 22–33. http://dx.doi.org/10.1109/mcg.2011.62.

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43

Gendrin, C., C. Weber, M. Figl, D. Georg, H. Bergmann, and W. Birkfellner. "FAST 2D/3D IMAGE REGISTRATION FOR ONLINE TUMOR TRACKING." Radiotherapy and Oncology 92 (August 2009): S172. http://dx.doi.org/10.1016/s0167-8140(12)73039-6.

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44

Kerkhoff, Yannic, and Stephan Block. "Analysis and refinement of 2D single-particle tracking experiments." Biointerphases 15, no. 2 (March 2020): 021201. http://dx.doi.org/10.1116/1.5140087.

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45

Weese, J., T. M. Buzug, G. P. Penney, and P. Desmedt. "2D/3D registration and motion tracking for surgical interventions." Philips Journal of Research 51, no. 2 (January 1998): 299–316. http://dx.doi.org/10.1016/s0165-5817(98)00007-2.

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46

Roecker, J. A. "Track monitoring when tracking with multiple 2D passive sensors." IEEE Transactions on Aerospace and Electronic Systems 27, no. 6 (1991): 872–76. http://dx.doi.org/10.1109/7.104247.

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47

Migniot, Cyrille, and Fakhreddine Ababsa. "Hybrid 3D–2D human tracking in a top view." Journal of Real-Time Image Processing 11, no. 4 (June 3, 2014): 769–84. http://dx.doi.org/10.1007/s11554-014-0429-7.

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48

Artioli, E., S. Marfia, and E. Sacco. "VEM-based tracking algorithm for cohesive/frictional 2D fracture." Computer Methods in Applied Mechanics and Engineering 365 (June 2020): 112956. http://dx.doi.org/10.1016/j.cma.2020.112956.

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49

Prabha, Hem, Guy Marleau, and Alain Hébert. "Tracking algorithms for multi-hexagonal assemblies (2D and 3D)." Annals of Nuclear Energy 69 (July 2014): 175–82. http://dx.doi.org/10.1016/j.anucene.2014.01.018.

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50

Peng, Xiao Ming. "Recent Progress in Human Face Detection, Tracking and Recognition." Advanced Materials Research 760-762 (September 2013): 1539–46. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1539.

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Facial recognition is an important research topic in biometrics and has wide applications in pattern recognition and computer vision. This paper aims at providing interested readers with recent progresses in human face detection, tracking, video-based face recognition, and 3D+2D hybrid face recognition. For this purpose, it mainly focuses on those state-of-the-arts methods and technologies that emerged in recent previous few years. Most existing methods in this area are still-image based which do not utilize motion information; whereas most video-based methods work only in 2D video sequences, which are subject to pose and illumination variations. The recent emergence of 3D video cameras capable of producing range image sequences and corresponding texture image sequences simultaneously allows for the possibility of facial recognition in a 3D+2D video-based scenario. In view of this fact, a scheme of face detection, tracking and recognition process in 3D video-based manner is also proposed in this paper with further concerns addressed.

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