International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / In this paper, a new coherent correlation-loop architecture for tracking direct-sequence spread-spectrum signals is proposed. In the proposed correlation loop model, the mean-square tracking error is minimized by varying the cross-correlation function between the received signal and the locally generated signal. The locally generated signal is produced by passing a replica of the transmitted signal through a linear time-invariant filter, which is termed the VCC filter. The issue of bandwidth of a correlation loop is addressed and a bandwidth definition for comparative purposes is introduced. The filter characteristics to minimize the tracking errors are determined using numerical optimization algorithms. This work demonstrates that the amplitude response of the VCC filter is a function of the input signal-to-noise ratio (SNR). In particular, the optimum filter does not replicate a differentiator at finite signal-to-noise ratio as is sometimes assumed. The optimal filter characteristics and the knowledge of the input SNR can be combined to produce a device that has very low probability of loosing lock.

The tabu search particle filter is proposed in this research based on the integration of the modified tabu search metaheuristic optimization and the genetic particle filter. Experiments with this algorithm in real time human tracking applications in unconstrained environments show that it is more robust, accurate and faster than a number of other existing metaheuristic filters, including the evolution particle filter, particle swarm filter, simulated annealing filter, path relink filter and scatter search filter. Quantitative evaluation illustrates that even with only ten particles in the system, the proposed tabu search particle filter has a success rate of 93.85% whereas the success rate of other metaheuristic filters ranged from 68.46% to 17.69% under the same conditions. The accuracy of the proposed algorithm (with ten particles in the tracking system) is 2.69 pixels on average, which is over 3.85 times better than the second best metaheuristic filters in accuracy and 18.13 times better than the average accuracy of all other filters. The proposed algorithm is also the fastest among all metaheuristic filters that have been tested. It achieves approximately 50 frames per second, which is 1.5 times faster than the second fastest algorithm and nineteen times faster than the average speed of all other metaheuristic filters. Furthermore, a unique colour sequence model is developed in this research based on a degenerated form of the hidden Markov model. Quantitative evaluations based on rigid object matching experiments illustrate that the successful matching rate is 5.73 times better than the widely used colour histogram. In terms of speed, the proposed algorithm achieves twice the successful matching rate in about three quarters of the processing time consumed by the colour histogram model. Overall, these results suggest that the two proposed algorithms would be useful in many applications due to their efficiently, accuracy and ability to robustly track people and coloured objects.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / A computational system was developed to support data collection for advanced airborne technology research. Basic research is conducted using a variety of sensing devices for collection of flight characteristics data from aircraft. To maximize control over as many variables as possible during research activities, a controlled aircraft tracking environment is needed to provide reference data for real-time operation and post-mission analysis. The solution to this requirement is realized with the ACMI Interface System (ACINTS). The ACINTS extracts real-time tracking data from a closed-loop telemetered tracking array, reprocesses needed parameters, provides reference data (positioning and control commands) to the sensor device, and records aircraft kinematics for later correlation with other collected data.

In this thesis we explore several algorithms for automatic real-time tracking of a tennis ball. We first investigate the use of background subtraction with color/shape recognition for fast tracking of the tennis ball. We then compare our solution with a cascade of boosted Haar classifiers [68] in a simulated environment to estimate the accuracy and ideal processing speeds. The results show that background subtraction techniques were not only faster but also more accurate than Haar classifiers. Following these promising results, we extend the background subtraction and develop other three improved techniques. These techniques use more accurate background models, more reliable and stringent criteria. They allow us to track the tennis ball in a real tennis environment with cameras having higher resolutions and frame rates. <p>We tested our techniques with a large number of real tennis videos. In the indoors environment, We achieved a true positive rate of about 90%, a false alarm rate of less than 2%, and a tracking speed of about 20 fps. For the outdoors environment, the performance of our techniques is not as good as the indoors cases due to the complexity and instability of the outdoors environment. The problem can be solved by resetting our system such that the camera focuses mainly on the tennis ball. Therefore, the influence of the external factors is minimized.<p>Despite the existing limitations, our techniques are able to track a tennis ball with very high accuracy and fast speed which can not be achieved by most tracking techniques currently available. We are confident that the motion information generated from our techniques is reliable and accurate. Giving this promising result, we believe some real-world applications can be constructed.

In this thesis we explore several algorithms for automatic real-time tracking of a tennis ball. We first investigate the use of background subtraction with color/shape recognition for fast tracking of the tennis ball. We then compare our solution with a cascade of boosted Haar classifiers [68] in a simulated environment to estimate the accuracy and ideal processing speeds. The results show that background subtraction techniques were not only faster but also more accurate than Haar classifiers. Following these promising results, we extend the background subtraction and develop other three improved techniques. These techniques use more accurate background models, more reliable and stringent criteria. They allow us to track the tennis ball in a real tennis environment with cameras having higher resolutions and frame rates. <p>We tested our techniques with a large number of real tennis videos. In the indoors environment, We achieved a true positive rate of about 90%, a false alarm rate of less than 2%, and a tracking speed of about 20 fps. For the outdoors environment, the performance of our techniques is not as good as the indoors cases due to the complexity and instability of the outdoors environment. The problem can be solved by resetting our system such that the camera focuses mainly on the tennis ball. Therefore, the influence of the external factors is minimized.<p>Despite the existing limitations, our techniques are able to track a tennis ball with very high accuracy and fast speed which can not be achieved by most tracking techniques currently available. We are confident that the motion information generated from our techniques is reliable and accurate. Giving this promising result, we believe some real-world applications can be constructed.

The application of augmented reality (AR) technology for assembly guidance is a novel approach in the traditional manufacturing domain. In this paper, we propose an AR approach for assembly guidance using a virtual interactive tool that is intuitive and easy to use. The virtual interactive tool, termed the Virtual Interaction Panel (VirIP), involves two tasks: the design of the VirIPs and the real-time tracking of an interaction pen using a Restricted Coulomb Energy (RCE) neural network. The VirIP includes virtual buttons, which have meaningful assembly information that can be activated by an interaction pen during the assembly process. A visual assembly tree structure (VATS) is used for information management and assembly instructions retrieval in this AR environment. VATS is a hierarchical tree structure that can be easily maintained via a visual interface. This paper describes a typical scenario for assembly guidance using VirIP and VATS. The main characteristic of the proposed AR system is the intuitive way in which an assembly operator can easily step through a pre-defined assembly plan/sequence without the need of any sensor schemes or markers attached on the assembly components. / Singapore-MIT Alliance (SMA)

Twin-to-twin transfusion syndrome (TTTS) is a complication of blood flow among fetuses sharing a single placenta. TTTS is associated with high mortality rates; however there is treatment available which significantly increases the rate of survival. The treatment procedure is although far from perfect. Limited by a narrow field of view, it is a challenging task for the surgeon to mentally visualize the vascular structures of the placenta while trying to navigate across the areas of interest. Previous research within both medical imaging and tracking technologies has been conducted but there is no perfect solution on how to solve these issues. This paper is part of a two-part project attempting to provide an application which can make the surgical procedure easier. The two parts are image stitching and real-time tracking, this paper focusing on the latter. This is done by choosing an appropriate tracking method which can provide location and orientation of a small sensor. The 3D data gathered from the sensor is processed by various transformations so that the bounding box of the camera movement can be mapped directly onto the image generated by the stitching process. The same transformations are applied to data collected from the sensor at a rate of 60 Hz, resulting in a responsive system. By comparing the x-value and y-value of a calculated point to the bounding box, this point can be converted to its corresponding pixel in the image. The system is responsive and by visually comparing the digital position in the image to its corresponding real world position it seems accurate enough, even though a few pixels misalignment will occur. / Tvillingstransfusionssyndrom (TTTS) är en komplikation av blodflöde som kan uppstå hos foster som delar placenta. TTTS associeras medhöga dödstal, emellertid finns det behandlingar som signifikant ökar chanserna för fostrens överlevnad. Behandlingsprocessen är docklångt ifrån perfekt. Begränsad av ett smalt synfält är det en utmanande uppgift för kirurgen att mentalt föreställa sig placentansvaskulärsystem samtidigt som denne försöker att navigera mellan alla intresseområden. Forskning inom både bildbehandling ochspårningsteknologier är inget främmande men det finns ännu ingen självklar lösning på dessa problem. Den här rapporten är en del av etttvåstegsprojekt vars mål är att framställa en applikation som kan underlätta behandlingen. De två delarna är image stitching ochrealtidsspårning, där den här rapporten fokuserar på det sistnämnda. Detta görs genom att välja en lämplig spårningsmetod som kan mätabåde position samt orientering av en sensor. 3D-datan från sensorn behandlas av olika matematiska transformationer så att denomskrivande rektangeln av kamerans rörelser kan placeras på bilden erhållen från stitchingprocessen. På samma sätt behandlas deninformation som hämtas från sensorn i realtid med en frekvens på 60 Hz, vilket resulterar i ett snabbreagerande system. Genom att jämförax-värde och y-värde från en beräknad punkt med den omskrivande rektangeln, kan den här punkten översättas till sin motsvarande pixel ibilden. Systemet reagerar snabbt på indata och genom att visuellt jämföra den digitala positionen i bilden mot den motsvarande positionen iden riktiga världen ger systemet ett tillfredställande resultat, även om punkten kommer att ha ett par pixlars felmarginal.

Nowadays, every single company needs to operate with large amount of data to support daily operation. Although there is pretty good market offer with information systems for managing various kinds of data, only small part of them is suitable for the company that does not deal with sale of goods but provides services, particularly marketing services or IT services (e.g. programming). This thesis describes the design and development of such a system which has a main goal to satisfy the needs of small to medium companies whose needs are still different than what currently marketed products can offer. Such a system will, apart from other functions, be able to manage projects and track work time of employees.

Les données billettiques sont de plus en plus utilisées pour l'analyse de la mobilité dans les transports en commun. Leur richesse spatiale et temporelle ainsi que leur volume, en font un bon matériel pour une meilleure compréhension des habitudes des usagers, pour prédire les flux de passagers ou bien encore pour extraire des informations sur les événements atypiques (ou anomalies), correspondant par exemple à un accroissement ou à une baisse inhabituelle du nombre de validations enregistrées sur le réseau.Après une présentation des travaux ayant été menés sur les données billettiques, cette thèse s'est attachée à développer de nouveaux outils de traitement de ces données. Nous nous sommes particulièrement intéressés à deux challenges nous semblant non encore totalement résolus dans la littérature : l'aide à la mise en qualité des données et la modélisation et le suivi des habitudes temporelles des usagers.Un des principaux challenges de la mise en qualité des données consiste en la construction d'une méthodologie robuste qui soit capable de détecter des plages de données potentiellement problématique correspondant à des situations atypiques et ce quel que soit le contexte (jour de la semaine, vacances, jours fériés, ...). Pour cela une méthodologie en deux étapes a été déployée, à savoir le clustering pour la détermination du contexte et la détection d'anomalies. L'évaluation de la méthodologie proposée a été entreprise sur un jeu de données réelles collectées sur le réseau de transport en commun rennais. En croisant les résultats obtenus avec les événements sociaux et culturels de la ville, l'approche a permis d'évaluer l'impact de ces événements sur la demande en transport, en termes de sévérité et d'influence spatiale sur les stations voisines.Le deuxième volet de la thèse concerne la modélisation et le suivi de l'activité temporelle des usagers. Un modèle de mélange de gaussiennes a été développé pour partitionner les usagers dans les clusters en fonction des heures auxquelles ils utilisent les transports en commun. L'originalité de la méthodologie proposée réside dans l'obtention de profils temporels continus pour décrire finement les routines temporelles de chaque groupe d'usager. Les appartenance aux clusters ont également été croisées avec les données disponibles sur les usagers (type de carte) en vue d'obtenir une description plus précise de chaque cluster. L'évolution de l'appartenance aux clusters au cours des années a également été analysée afin d'évaluer la stabilité de l'utilisation des transports d'une année sur l'autre. / Ticketing logs are being increasingly used to analyse mobility in public transport. The spatial and temporal richness as well as the volume of these data make them useful for understanding passenger habits and predicting origin-destination flows. Information on the operations carried out on the transportation network can also be extracted in order to detect atypical events (or anomalies), such as an unusual increase or decrease in the number of validations.This thesis focuses on developing new tools to process ticketing log data. We are particularly interested in two challenges that seem to be not yet fully resolved in the literature: help with data quality as well as the modeling and monitoring of passengers' temporal habits.One of the main challenges in data quality is the construction of a robust methodology capable of detecting atypical situations in any context (day of the week, holidays, public holidays, etc.). To this end, two steps were deployed, namely clustering for context estimation and detection of anomalies. The evaluation of the proposed methodology is conducted on a real dataset collected on the Rennes public transport network. By cross-comparing the obtained results with the social and cultural events of the city, it is possible to assess the impact of these events on transport demand, in terms, of severity and spatial influence on neighboring stations.The second part of the thesis focuses on the modeling and the tracking of the temporal activity of passengers. A Gaussian mixture model is proposed to partition passengers into clusters according to the hours they use public transport. The originality of the methodology compared to existing approaches lies in obtaining continuous time profiles in order to finely describe the time routines of each passenger cluster. Cluster memberships are also cross-referenced with passenger data (card type) to obtain a more accurate description of each cluster. The cluster membership over the years has also been analyzed in order to study how the use of transport evolves

In the prevailing industrial revolution, most industries are on the path towards the digitalization journey. To incorporate several digital technologies in the organization data reliability and accuracy act as key enablers. To achieve the set goals, the connectivity of the machines is considered a prominent endeavour. Such connectivity can be achieved by implementing IIOT technology, the connected IIOT architecture enables interoperability, where the computerized machine can seamlessly communicate and transfer information among them. The purpose of this study was to examine the potential impacts of integrating IIOT into the organizational framework and further explore the advantages gained in terms of productivity and maintenance. This intended study concentrated on the welding department in VCE and prioritized specific robots for the research. In addition, to improve the connectivity and visualize the data a customizable dashboard was created to facilitate real-time tracking of the robots and an alert system was developed to notify the problems in real-time. To carry out the study this research was intended to use a particular IIOT software Thingworx from the PTC community. The research was carried out with extensive interviews and personal observation on the shop floor following a qualitative analysis methodology. Through the interviews, the prioritized entities were focused and based on the end user’s requirement the selected data tags were visualized. Furthermore, the findings from the research were analyzed and discussed on how IIOT technology could potentially benefit an organization is presented. / I den rådande industriella revolutionen är de flesta industrier på väg mot digitaliseringsresan. Att införliva flera digitala teknologier i organisationen fungerar datatillförlitlighet och noggrannhet som viktiga möjliggörare. För att uppnå de uppsatta målen anses maskinernas anslutningsmöjligheter vara en framträdande strävan. Sådan anslutning kan uppnås genom att implementera IIOT-teknik, vilket möjliggör interoperabilitet, där den datoriserade maskinen sömlöst kan kommunicera och överföra information mellan dem. Syftet med denna studie var att undersöka de potentiella effekterna av att integrera IIOT i det organisatoriska ramverket och ytterligare utforska fördelarna som uppnåddes i termer av produktivitet och underhåll. Denna tilltänkta studie koncentrerade sig på svetsavdelningen i VCE och prioriterade specifika robotar för forskningen. För att förbättra anslutningen och visualisera data skapades dessutom en anpassningsbar instrumentpanel för att underlätta realtidsspårning av robotarna och ett varningssystem utvecklades för att meddela problemen i realtid. För att genomföra studien var denna forskning avsedd att använda en speciell IIOT-programvara Thingworx från PTC-gemenskapen. Forskningen genomfördes med omfattande intervjuer och observation på verkstadsgolvet enligt en kvalitativ analysmetodik. Genom intervjuerna fokuserades de prioriterade enheterna och baserat på slutanvändarens krav visualiserades de valda datataggarna. Vidare har resultaten från forskningen analyserats och diskuterats om hur IIOT-teknik potentiellt skulle kunna gynna en organisation.