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Готові списки джерел за темами / Tracking 2D

Добірка наукової літератури з теми "Tracking 2D"

Автор: Grafiati

Опубліковано: 24 липня 2022

Оновлено: 8 серпня 2022

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Статті в журналах з теми "Tracking 2D":

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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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.

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.

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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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.

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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Більше джерел

Дисертації з теми "Tracking 2D":

1

Lebeda, Karel. "2D and 3D tracking and modelling." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/811206/.

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Visual tracking of unknown objects in unconstrained video-sequences is extremely challenging due to a number of unsolved issues. This thesis explores several of these and examines possible approaches to tackle them. The unconstrained nature of real-world input sequences creates huge variation in the appearance of the target object due to changes in pose and lighting. Additionally, the object can be occluded by either parts of itself, other elements of the scene, or the frame boundaries. Observations may also be corrupted due to low resolution, motion blur, large frame-to-frame displacement, or incorrect exposure or focus of the camera. Finally, some objects are inherently difficult to track due to their (low) texture, specular/transparent nature, non-rigid deformations, etc. Conventional trackers depend heavily on the texture of the target. This causes issues with transparent or untextured objects. Edge points can be used in cases where standard feature points are scarce; these however suffer from the aperture problem. To address this, the first contribution of this thesis explores the idea of virtual corners, using pairs of non-adjacent line correspondences, tangent to edges in the image. Furthermore, the chapter investigates the possibility of long-term tracking, introducing a re-detection scheme to handle occlusions while limiting drift of the object model. The outcome of this research is an edge-based tracker, able to track in scenarios including untextured objects, full occlusions and significant length. The tracker, besides reporting excellent results in standard benchmarks, is demonstrated to successfully track the longest sequence published to date. Some of the issues in visual tracking are caused by suboptimal utilisation of the image information. The object of interest can easily occupy as few as ten or even one percent of the video frame area. This causes difficulties in challenging scenarios such as sudden camera shakes or full occlusions. To improve tracking in such cases, the next major contribution of this thesis explores relationships within the context of visual tracking, with a focus on causality. These include causal links between the tracked object and other elements of the scene such as the camera motion or other objects. Properties of such relationships are identified in a framework based on information theory. The resulting technique can be employed as a causality-based motion model to improve the results of virtually any tracker. Significant effort has previously been devoted to rapid learning of object properties on the fly. However, state-of-the-art approaches still often fail in cases such as rapid out-of-plane rotations, when the appearance changes suddenly. One of the major contributions of this thesis is a radical rethinking of the traditional wisdom of modelling 3D motion as appearance change. Instead, 3D motion is modelled as 3D motion. This intuitive but previously unexplored approach provides new possibilities in visual tracking research. Firstly, 3D tracking is more general, as large out-of-plane motion is often fatal for 2D trackers, but helps 3D trackers to build better models. Secondly, the tracker’s internal model of the object can be used in many different applications and it could even become the main motivation, with tracking supporting reconstruction rather than vice versa. This effectively bridges the gap between visual tracking and Structure from Motion. The proposed method is capable of successfully tracking sequences with extreme out-of-plane rotation, which poses a considerable challenge to 2D trackers. This is done by creating realistic 3D models of the targets, which then aid in tracking. In the majority of the thesis, the assumption is made that the target’s 3D shape is rigid. This is, however, a relatively strong limitation. In the final chapter, tracking and dense modelling of non-rigid targets is explored, demonstrating results in even more generic (and therefore challenging) scenarios. This final advancement truly generalises the tracking problem with support for long-term tracking of low texture and non-rigid objects in sequences with camera shake, shot cuts and significant rotation. Taken together, these contributions address some of the major sources of failure in visual tracking. The presented research advances the field of visual tracking, facilitating tracking in scenarios which were previously infeasible. Excellent results are demonstrated in these challenging scenarios. Finally, this thesis demonstrates that 3D reconstruction and visual tracking can be used together to tackle difficult tasks.

2

Trache, Marian Tudor. "The agreement between 3D, standard 2D and triplane 2D speckle tracking: effects of image quality and 3D volume rate." Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-202530.

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Die technologische Entwicklung im Bereich der Echokardiographie hat in der letzten Dekade neue Methoden zur objektiven Erfassung der regionalen linksventrikulären Wandbewegung ermöglicht. Speckle Tracking erfasst die myokardiale Deformation durch die Positionsänderung einzelner Bildpunkte von einem Bild des analysierten Datensatzes zum nächsten. Diese Methode ist dem Gewebedoppler überlegen, insbesondere wegen ihrer Unabhängigkeit vom Anlotungswinkel. Zwei-dimensionale (2D) Speckle Tracking Analysen wurden für die klinische Praxis validiert. Die drei-dimensionale (3D) Echokardiographie erlaubt inzwischen Speckle Tracking Analysen von 3D Datensätzen, welche jedoch für die klinische Praxis noch nicht ausreichend validiert sind. Bei Patienten mit normaler regionaler linksventrikulärer Wandbewegung (N=37), sowie bei Patienten mit ischämie-bedingten Wandbewegungsstörungen (N=18) wurden 3D und 2D Speckle Tracking Analysen durchgeführt. Die Vergleichbarkeit der beiden Methoden hinschtlich der Quantifizierung von normalen und pathologischen Wandbewegungsmustern wurde anhand dieser Messungen geprüft. Des weiteren wurde der Einfluss der Bildrate und Bildqualität drei-dimensionaler Datensätze auf die Vergleichbarkeit beider Methoden analysiert. Es zeigte sich eine gute Vergleichbarkeit des 2D und 3D Speckle Tracking in der Diagnostik eingeschränkter linksventrikulärer systolischer Funktion, sowie in der Lokalisationsdiagnostik umschriebener Wandbewegungsstörungen. 2D und 3D Speckle Tracking sind jedoch noch nicht als gleichwertige Methoden anzusehen. Die Bildqualität, generell bei beiden Modalitäten - jedoch speziell bei 3D Datensätzen, sowie die Bildrate der 3D Datensätze zeigen signifikante Einflüsse auf die 3D Strain Analysen. Eine korrekte Standardisierung der analysierten Aufnahmen und eine optimale Bildqualität sind wichtige Faktoren, die die Zuverlässigkeit des 2D und 3D Speckle Trackings bestimmen.

3

Ren, Yuheng. "Implicit shape representation for 2D/3D tracking and reconstruction." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:c70dc663-ee7c-4100-b492-3a85bf8640d1.

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This thesis develops and describes methods for real-time tracking, segmentation and 3-dimensional (3D) model acquisition, in the context of developing games for stroke patients that are rehabilitating at home. Real-time tracking and reconstruction of a stroke patient's feet, hands and the control objects that they are touching can enable not only the graphical visualization of the virtual avatar in the rehabilitation games, but also permits measurement of the patient's performs. Depth or combined colour and depth imagery from a Kinect sensor is used as input data. The 3D signed distance function (SDF) is used as implicit shape representation, and a series of probabilistic graphical models are developed for the problem of model-based 3D tracking, simultaneous 3D tracking and reconstruction and 3D tracking of multiple objects with identical appearance. The work is based on the assumption that the observed imagery is generated jointly by the pose(s) and the shape(s). The depth of each pixel is randomly and independently sampled from the likelihood of the pose(s) and the shape(s). The pose(s) tracking and 3D shape reconstruction problems are then cast as the maximum likelihood (ML) or maximum a posterior (MAP) estimate of the pose(s) or 3D shape. This methodology first leads to a novel probabilistic model for tracking rigid 3D objects with only depth data. For a known 3D shape, optimization aims to find the optimal pose that back projects all object region pixels onto the zero level set of the 3D shape, thus effectively maximising the likelihood of the pose. The method is extended to consider colour information for more robust tracking in the presence of outliers and occlusions. Initialised with a coarse 3D model, the extended method is also able to simultaneously reconstruct and track an unknown 3D object in real time. Finally, the concept of `shape union' is introduced to solve the problem of tracking multiple 3D objects with identical appearance. This is formulated as the minimum value of all SDFs in camera coordinates, which (i) leads to a per-pixel soft membership weight for each object thus providing an elegant solution for the data association in multi-target tracking and (ii) it allows for probabilistic physical constraints that avoid collisions between objects to be naturally enforced. The thesis also explore the possibility of using implicit shape representation for online shape learning. We use the harmonics of 2D discrete cosine transform (DCT) to represent 2D shapes. High frequency harmonics are decoupled from low ones to represent the coarse information and the details of the 2D shape. A regression model is learnt online to model the relationship between the high and low frequency harmonics using Locally Weighted Projection Regression (LWPR). We have demonstrated that the learned regression model is able to detect occlusion and recover them to the complete shape.

4

Yang, Po. "Accuracy improvement of RFID based 2D tracking and localisation." Thesis, Staffordshire University, 2011. http://eprints.staffs.ac.uk/1884/.

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The purpose of localization and tracking technology in indoor application is to extract moving object parameters accurately and precisely. This thesis investigates the problem of how to utilize RFID technique for the accurate and precise extraction of indoor 2D moving object position parameters. Firstly, a framework named RFID-Loc with three modules: RFID-Loc Infrastructure, RFID-Loc Data Filter and RFID-Loc Localisation Algorithm, is established from a theoretical perspective. This framework can guide the research and design of methods used in an RFID based object localisation system with enhanced localisation accuracy and precision. Secondly, from practical perspective, few methods are proposed in RFID-Loc framework to improve the localisation accuracy and precision. A sparse RFID Tag Arrangement strategy is proposed in this RFID-Loc framework, aiming at reducing the impacts of regular false reading error from RFID infrastructure level on localisation precision. The efficiency of this methods and the assumptions upon which it relies, are investigated empirically. A rectangle-based feature selection method is justified as the major RFID Data Filter algorithm, with the capability of maximally reducing regular false reading errors. The possibility to resist unexpected false reading error in an RFID-Loc system is investigated by discussing and comparing several RFID-based localisation algorithms. A dynamic localisation algorithm for RFID-Loc system is proposed to accurately and precisely extract moving object position parameters overtime in an RFID-Loc system. This algorithm is shown to have a better capability of resisting unexpected false reading error than conventional localisation algorithms used in RFID-based localisation systems, while having a higher computational complexity. By following the theoretical guidelines in RFID-Loc framework and implementing the proposed methods, the experimental results demonstrate that the localisation accuracy and precision can be significantly improved, up to 10 centimetres and 3 centimetres under current RFID devices.

5

Popov, Pavel Alexandrovich. "Real-time 2D Static Hand Gesture Recognition and 2D Hand Tracking for Human-Computer Interaction." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41556.

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The topic of this thesis is Hand Gesture Recognition and Hand Tracking for user interface applications. 3 systems were produced, as well as datasets for recognition and tracking, along with UI applications to prove the concept of the technology. These represent significant contributions to resolving the hand recognition and tracking problems for 2d systems. The systems were designed to work in video only contexts, be computationally light, provide recognition and tracking of the user's hand, and operate without user driven fine tuning and calibration. Existing systems require user calibration, use depth sensors and do not work in video only contexts, or are computationally heavy requiring GPU to run in live situations. A 2-step static hand gesture recognition system was created which can recognize 3 different gestures in real-time. A detection step detects hand gestures using machine learning models. A validation step rejects false positives. The gesture recognition system was combined with hand tracking. It recognizes and then tracks a user's hand in video in an unconstrained setting. The tracking uses 2 collaborative strategies. A contour tracking strategy guides a minimization based template tracking strategy and makes it real-time, robust, and recoverable, while the template tracking provides stable input for UI applications. Lastly, an improved static gesture recognition system addresses the drawbacks due to stratified colour sampling of the detection boxes in the detection step. It uses the entire presented colour range and clusters it into constituent colour modes which are then used for segmentation, which improves the overall gesture recognition rates. One dataset was produced for static hand gesture recognition which allowed for the comparison of multiple different machine learning strategies, including deep learning. Another dataset was produced for hand tracking which provides a challenging series of user scenarios to test the gesture recognition and hand tracking system. Both datasets are significantly larger than other available datasets. The hand tracking algorithm was used to create a mouse cursor control application, a paint application for Android mobile devices, and a FPS video game controller. The latter in particular demonstrates how the collaborating hand tracking can fulfill the demanding nature of responsive aiming and movement controls.

6

Stüer, Katharina [Verfasser]. "Echokardiografische Funktionsanalyse des linken Vorhofes mittels 2D-Speckle Tracking / Katharina Stüer." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2015. http://d-nb.info/1075493129/34.

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7

Simonnet, Damien Remi Jules Joseph. "Detecting and tracking humans in crowded scenes based on 2D image understanding." Thesis, Kingston University, 2012. http://eprints.kingston.ac.uk/28213/.

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Tracking pedestrians in surveillance videos is an important task, not only in itself but also as a component of pedestrian counting, activity and event recognition, and scene understanding in general. Robust tracking in crowded environments remains a major challenge, mainly due to the occlusions and interactions between pedestrians. Methods to detect humans in a single frame are becoming increasingly accurate. Therefore, the majority of multi-target tracking algorithms in crowds follow a tracking-by-detection approach, along with models of individual and group behaviour, and various types of features to re-identify any given pedestrian (and discriminate them from the remainder). The aim is, given a Closed Circuit TeleVision (CCTV) camera view (moving or static) of a crowded scene, to produce tracks that indicate which pedestrians are entering and leaving the scene to be used in further applications (e.g. a multi-camera tracking scenario). Therefore, this output should be accurate in terms of position, have few false alarms and identity changes (i.e. tracks have not to be fragmented nor switch identity). Consequently, the presented algorithm concentrates on two important characteristics. Firstly, production of a real-time or near real-time output to be practically usable for further applications without penalising the final system. Secondly, management of occlusions which is the main challenge in crowds. The methodology presented, based on a tracking-by-detection approach, proposes an advance over those two aspects through a hierarchical framework to solve short and long occlusions with two novel methods. First, at a fine temporal scale, kinematic features and appearance features based on non-occluded parts are combined to generate short and reliable 'tracklets'. More specifically, this part uses an occlusion map which attributes a local measurement (by searching over the non-occluded parts) to a target without a global measurement (i.e. a measurement generated by the global detector), and demonstrates better results in terms of tracklet length without generating more false alarms or identity changes. Over a longer scale, these tracklets are associated with each other to build up longer tracks for each pedestrian in the scene. This tracklet data association is based on a novel approach that uses dynamic time warping to locate and measure the possible similarities of appearances between tracklets, by varying the time step and phase of the frame-based visual feature. The method, which does not require any target initialisations or camera calibrations, shows significant improvements in terms of false alarms and identity changes, the latter being a critical point for evaluating tracking algorithms. The evaluation framework, based on different metrics introduced in the literature, consists of a set of new track-based metrics (in contrast to frame-based) which enables failure parts of a tracker to be identified and algorithms to be compared as a single value. Finally, advantages of the dual method proposed to solve long and short occlusions are to reduce simultaneously the problem of track fragmentation and identity switches, and to make it naturally extensible to a multi-camera scenario. Results are presented as a tag and track system over a network of moving and static cameras. In addition to public datasets for multi-target tracking in crowds (e.g. Oxford Town Centre (OTC) dataset) where the new methodology introduced (i.e. building tracklets based on non-occluded pedestrian parts plus re-identification with dynamic time warping) shows significant improvements. Two new datasets are introduced to test the robustness of the algorithm proposed in more challenging scenarios. Firstly, a CCTV shopping view centre is used to demonstrate the effectiveness of the algorithm in a more crowded scenario. Secondly, a dataset with a network of CCTV Pan Tilt Zoom (PTZ) cameras tracking a single pedestrian, demonstrates the capability of the algorithm to handle a very difficult scenario (abrupt motion and non-overlapping camera views) and therefore its applicability as a component of a multitarget tracker in a network of static and PTZ cameras. The thesis concludes with a critical analysis of the work and presents future research opportunities (notably the use of this framework in a non-overlapping network of static and PTZ cameras).

8

Recatalá, Ballester Gabriel. "Visual determination, tracking and execution of 2D grasps using a behavior-inspired approach." Doctoral thesis, Universitat Jaume I, 2003. http://hdl.handle.net/10803/10371.

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This thesis focuses on the definition of a task for the determination, tracking and execution of a grasp on an unknown object. In particular, it is considered the case in which the object is ideally planar and the grasp has to be executed with a two-fingered, parallel-jaw gripper using vision as the source of sensor data. For the specification of this task, an architecture is defined that is based on three basic components -virtual sensors, filters, and actuators-, which can be connected to define a control loop. Each step in this task is analyzed separately, considering several options in some cases.
Some of the main contributions of this thesis include: (1) the use of a modular approach to the specification of a control task that provides a basic framework for supporting the concept of behavior; (2) the analysis of several strategies for obtaining a compact representation of the contour of an object; (3) the development of a method for the evaluation and search of a grasp on a planar object for a two-fingered gripper; (4) the specification of different representations of a grasp and the analysis of their use for tracking the grasp between different views of an object; (5) the specification of algorithms for the tracking of a grasp along the views of an object obtained from a sequence of single images and a sequence of stereo images; (6) the definition of parametrized models of the target position of the grasp points and of the feasibility of this target grasp, and of an off-line procedure for the computation of some of the reference values required by this model; and (7) the definition and analysis of a visual servoing control scheme to guide the gripper of a robot arm towards an unknown object using the grasp points computed for that object as control features.

9

Mirpour, Sasha. "A Comparison of 3D Camera Tracking Software." Thesis, University of Gävle, Department of Mathematics, Natural and Computer Sciences, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-779.

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In the past decade computer generated images have become widely used in the visual effects industry. One of the main reasons is being able to seamlessly blend three dimensional (3D) animation with live-action footage. In this study, different 3D camera tracking software (also referred to as matchmoving) is compared focusing on workflow, user-friendly system, and quality of production.

10

Minetto, Rodrigo 1983. "Reconhecimento de texto e rastreamento de objetos 2D/3D." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275708.

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Orientadores: Jorge Stolfi, Neucimar Jerônimo Leite
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Computação
Made available in DSpace on 2018-08-20T03:12:07Z (GMT). No. of bitstreams: 1 Minetto_Rodrigo_D.pdf: 35894128 bytes, checksum: 8a0e453fba7e6a9a02fb17a52fdbf878 (MD5) Previous issue date: 2012
Resumo: Nesta tese abordamos três problemas de visão computacional: (1) detecção e reconhecimento de objetos de texto planos em imagens de cenas reais; (2) rastreamento destes objetos de texto em vídeos digitais; e (3) o rastreamento de um objeto tridimensional rígido arbitrário com marcas conhecidas em um vídeo digital. Nós desenvolvemos, para cada um dos problemas, algoritmos inovadores, que são pelo menos tão precisos e robustos quanto outros algoritmos estado-da-arte. Especificamente, para reconhecimento de texto nós desenvolvemos (e validamos extensivamente) um novo descritor de imagem baseado em HOG especializado para escrita romana, que denominamos T-HOG, e mostramos sua contribuição como um filtro em um detector de texto (SNOOPERTEXT). Nós também melhoramos o algoritmo SNOOPERTEXT através do uso da técnica multiescala para tratar caracteres de tamanhos bastante variados e limitar a sensibilidade do algoritmo a vários artefatos. Para rastreamento de texto, nós descrevemos quatro estratégias básicas para combinar a detecção e o rastreamento de texto, e desenvolvemos também um rastreador específico baseado em filtro de partículas que explora o uso do reconhecedor T-HOG. Para o rastreamento de objetos rígidos, nós desenvolvemos um novo algoritmo preciso e robusto (AFFTRACK) que combina rastreamento de características por KLT com uma calibração de câmera melhorada. Nós testamos extensivamente nossos algoritmos com diversas bases de dados descritas na literatura. Nós também desenvolvemos algumas bases de dados (publicamente disponíveis) para a validação de algoritmos de detecção e rastreamento de texto e de rastreamento de objetos rígidos em vídeos
Abstract: In this thesis we address three computer vision problems: (1) the detection and recognition of flat text objects in images of real scenes; (2) the tracking of such text objects in a digital video; and (3) the tracking an arbitrary three-dimensional rigid object with known markings in a digital video. For each problem we developed innovative algorithms, which are at least as accurate and robust as other state-of-the-art algorithms. Specifically, for text classification we developed (and extensively evaluated) a new HOG-based descriptor specialized for Roman script, which we call T-HOG, and showed its value as a post-filter for an existing text detector (SNOOPERTEXT). We also improved the SNOOPERTEXT algorithm by using the multi-scale technique to handle widely different letter sizes while limiting the sensitivity of the algorithm to various artifacts. For text tracking, we describe four basic ways of combining a text detector and a text tracker, and we developed a specific tracker based on a particle-filter which exploits the T-HOG recognizer. For rigid object tracking we developed a new accurate and robust algorithm (AFFTRACK) that combines the KLT feature tracker with an improved camera calibration procedure. We extensively tested our algorithms on several benchmarks well-known in the literature. We also created benchmarks (publicly available) for the evaluation of text detection and tracking and rigid object tracking algorithms
Doutorado
Ciência da Computação
Doutor em Ciência da Computação

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Книги з теми "Tracking 2D":

1

Edwards, J. B. Tracking the features of a spatially distributed continuous field: (the idealised 2D,deterministic case). Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1994.

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2

Tribouilloy, Christophe, Patrizio Lancellotti, Ferande Peters, José Juan Gómez de Diego, and Luc A. Pierard. Heart valve disease (aortic valve disease): aortic regurgitation. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198726012.003.0033.

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Echocardiography is the cornerstone examination for the assessment of aortic regurgitation (AR): it provides reliable evaluation of the aortic valve and allows diagnosis and identification of the mechanism of regurgitation. The specific aetiology of the disease can be identified in the majority of cases. A combination of quantitative and quantitative Doppler and two-dimensional (2D) echocardiographic parameters allows the evaluation of the severity of AR and determination of the haemodynamic and left ventricular function repercussions. Echocardiography allows the detection of associated lesions of the aortic root or other valves. In symptomatic patients, echocardiography is essential to confirm the severity of AR. In asymptomatic patients with moderate or severe AR, echocardiography is essential for regular follow-up, by providing precise and reproducible measurements of LV dimensions and function, and for identifying patients who should be considered for elective surgical intervention. In most cases, transthoracic echocardiography (TTE) provides all of the necessary information and transoesophageal echocardiography in usually not required. Real-time three-dimensional (3D) TTE can be complementary to 2D echocardiography for the assessment of the mechanism and quantification of AR by increasing the level of confidence, especially when 2D echocardiographic data are inconclusive or discordant with clinical findings. Tissue Doppler imaging and especially the speckle tracking method are promising approaches to detect early LV dysfunction in patients with asymptomatic severe AR. Echocardiography is therefore the key examination for the assessment of AR and at the centre of the strategic discussion concerning the indications and timing of surgery.

3

Tourneau, Thierry Le, Luis Caballero, and Tsai Wei-Chuan. Right atrium. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198726012.003.0024.

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The right atrium (RA) is located on the upper right-hand side of the heart and has relatively thin walls. From an anatomical point of view, the RA comprises three basic parts, the appendage, the vestibule of the tricuspid valve, and the venous component (superior and inferior vena cava, and the coronary sinus) receiving the deoxygenated blood. The RA is a dynamic structure dedicated to receive blood and to assist right ventricular (RV) filling. The three components of atrial function are the reservoir function during ventricular systole, the conduit function which consists in passive blood transfer from veins to the RV in diastole, and the booster pump function in relation to atrial contraction in late diastole to complete ventricular filling. Right atrial function depends on cardiac rhythm (sinus or atrial fibrillation), pericardial integrity, RV load and function, and tricuspid function. Right atrial dimension assessment is limited in two-dimensional (2D) echocardiography. Right atrial planimetry in the apical four-chamber view is commonly used with an upper normal value of 18-20 cm2. Minor and major diameters can also be measured. Three-dimensional (3D) echocardiography could overcome the limitation of conventional echocardiography in assessing RA size. Right atrial function has been poorly explored by echocardiography both in physiological and pathological contexts. Although tricuspid inflow and tissue Doppler imaging of tricuspid annulus can be used in the exploration of RA function, 2D speckle tracking and 3D echocardiography appear promising tools to dissect RA function and to overcome the limitations of standard echocardiography.

Частини книг з теми "Tracking 2D":

1

Langmann, Benjamin. "Multiple Camera 2D/3D Tracking." In Wide Area 2D/3D Imaging, 111–23. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-06457-0_7.

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2

Ni, Zhenjiang, Céline Pacoret, Ryad Benosman, and Stéphane Régnier. "Asynchronous Event-Based 2D Microsphere Tracking." In Haptic Feedback Teleoperation of Optical Tweezers, 93–127. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119005070.ch3.

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3

Huwer, S., and H. Niemann. "2D-object tracking based on projection-histograms." In Computer Vision — ECCV'98, 861–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055709.

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4

Baert, S. A. M., and W. J. Niessen. "2D Guide Wire Tracking during Endovascular Interventions." In Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002, 101–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45787-9_13.

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5

Yöndem, Burak, Mustafa Unel, and Aytul Ercil. "2D Shape Tracking Using Algebraic Curve Spaces." In Computer and Information Sciences - ISCIS 2005, 698–707. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11569596_72.

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6

Kang, Woobum, and Shigeru Eiho. "3D Tracking Using 2D-3D Line Segment Correspondence and 2D Point Motion." In Communications in Computer and Information Science, 367–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75274-5_26.

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7

Para, Eric, Olivier Bernier, and Catherine Achard. "2D Articulated Body Tracking with Self-occultations Handling." In Articulated Motion and Deformable Objects, 156–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-70517-8_16.

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8

Urru, Andrea, Miguel Angel González Ballester, and Chong Zhang. "2D + Time Object Tracking Using Fiji and ilastik." In Computer Optimized Microscopy, 423–48. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9686-5_20.

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9

Lebeda, Karel, Simon Hadfield, and Richard Bowden. "2D or Not 2D: Bridging the Gap Between Tracking and Structure from Motion." In Computer Vision -- ACCV 2014, 642–58. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16817-3_42.

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10

Khelvas, Aleksander, Alexander Gilya-Zetinov, Egor Konyagin, Darya Demyanova, Pavel Sorokin, and Roman Khafizov. "Improved 2D Human Pose Tracking Using Optical Flow Analysis." In Advances in Intelligent Systems and Computing, 10–22. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55187-2_2.

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Тези доповідей конференцій з теми "Tracking 2D":

1

Banerjee, Partha P., Ujitha Abeywickrema, Haowen Zhou, Behzad Bordbar, Mohammad S. Alam, George Nehmetallah, Jed Khoury, and Liangcai Cao. "Taking correlation from 2D to 3D: optical methods and performance evaluation." In Pattern Recognition and Tracking XXX, edited by Mohammad S. Alam. SPIE, 2019. http://dx.doi.org/10.1117/12.2520309.

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2

Chung, Adrian James, Fani Deligianni, Xiao-Peng Hu, and Guang-Zhong Yang. "Visual feature extraction via eye tracking for saliency driven 2D/3D registration." In the Eye tracking research & applications symposium. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/968363.968371.

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3

Goldner, Eliana, Pedro Mário Silva, and Marcelo Gattass. "2D Horizon Tracking Using Dynamic Programming." In 13th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 26-29 August 2013. Society of Exploration Geophysicists and Brazilian Geophysical Society, 2013. http://dx.doi.org/10.1190/sbgf2013-328.

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4

Habermann, Danilo, and Claudio Garcia. "Obstacle Detection and Tracking Using Laser 2D." In 2010 Latin American Robotics Symposium and Intelligent Robotic Meeting (LARS). IEEE, 2010. http://dx.doi.org/10.1109/lars.2010.21.

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5

Brown, M., T. Drummond, and R. Cipolla. "3D Model Acquisition by Tracking 2D Wireframes." In British Machine Vision Conference 2000. British Machine Vision Association, 2000. http://dx.doi.org/10.5244/c.14.66.

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6

Li, Fengping, Dan Hart, Irshaad Fatadin, Robert Ferguson, Roberta Guilizzoni, and Stuart Harmon. "Characterisation of an Optical 2D Tracking System." In 2019 IEEE 2nd British and Irish Conference on Optics and Photonics (BICOP). IEEE, 2019. http://dx.doi.org/10.1109/bicop48819.2019.9059570.

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7

Quan Yuan, S. Sclaroff, and V. Athitsos. "Automatic 2D Hand Tracking in Video Sequences." In 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05). IEEE, 2005. http://dx.doi.org/10.1109/acvmot.2005.27.

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8

Toklu, Candemir, A. Murat Tekalp, and A. Tanju Erdem. "Semiautomatic video layering using 2D mesh tracking." In Photonics West '98 Electronic Imaging, edited by Sarah A. Rajala and Majid Rabbani. SPIE, 1998. http://dx.doi.org/10.1117/12.298313.

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9

"3D TRACKING USING 2D-3D LINE SEGMENT CORRESPONDENCE AND 2D POINT MOTION." In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0001365402780285.

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10

Zhang, Tinghua, Zhengyan Zhang, Botao Lin, Junnan Xue, Jiaole Wang, and Shuang Song. "Towards Tracking by 2D-target Registration for Surgical Optical Tracking System." In 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2021. http://dx.doi.org/10.1109/robio54168.2021.9739255.

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