abstract: The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban terrain environments is traditionally implemented using sequential Monte Carlo filtering algorithms and data association techniques. However, data association techniques can be computationally intensive and require very strict conditions for efficient performance. This thesis investigates the probability hypothesis density (PHD) method for tracking multiple targets in urban environments. The PHD is based on the theory of random finite sets and it is implemented using the particle filter. Unlike data association methods, it can be used to estimate the number of targets as well as their corresponding tracks. A modified maximum-likelihood version of the PHD (MPHD) is proposed to automatically and adaptively estimate the measurement types available at each time step. Specifically, the MPHD allows measurement-to-nonlinearity associations such that the best matched measurement can be used at each time step, resulting in improved radar coverage and scene visibility. Numerical simulations demonstrate the effectiveness of the MPHD in improving tracking performance, both for tracking multiple targets and targets in clutter. / Dissertation/Thesis / M.S. Electrical Engineering 2011

Value based decisions are among the most common types of decisions made by humans. A considerable body of work has investigated how different types of information guide such decisions, as well as how evaluations of their outcomes retroactively inform the parameters that were used to inform them. Several open questions remain regarding the nature of the underlying representations of decision-relevant information. Of particular relevance is whether or not positive and negative information (i.e. rewards/gains vs. punishments/losses/costs) are treated as categorically distinct, or whether they are represented on a common scale. This question was examined across three different studies utilizing a variety of methods (traditional event-related potentials, multivariate pattern classification, and eye tracking) to obtain a more comprehensive picture of how decision-relevant information is represented A common theme among the three studies was that positive and negative types of information seems to be, at least initially, represented as categorically distinct (whether it be information about gains vs. losses, or value vs. effort). Additionally, integration of different types of information appears to take place during the later phases of the decision period, which may also be when distortions in the representation of value information (ex. loss aversion) may occur. Overall, this body of work advances our understanding of the underpinnings of value based decisions by providing additional insight about how decision-relevant information is represented in a dynamic and flexible manner.

The research contributes to the field of video analysis by proposing novel approaches to automatically generating human observer performance patterns that can be effectively used in advancing the modern video analytic and forensic algorithms. Eye tracker and eye movement analysis technology are employed in medical research, psychology, cognitive science and advertising. The data collected on human eye movement from the eye tracker can be analyzed using the machine and statistical learning approaches. Therefore, the study attempts to understand the visual attention pattern of people when observing a captured CCTV footage. It intends to prove whether the eye gaze of the observer which determines their behaviour is dependent on the given instructions or the knowledge they learn from the surveillance task. The research attempts to understand whether the attention of the observer on human objects is differently identified and tracked considering the different areas of the body of the tracked object. It attempts to know whether pattern analysis and machine learning can effectively replace the current conceptual and statistical approaches to the analysis of eye-tracking data captured within a CCTV surveillance task. A pilot study was employed that took around 30 minutes for each participant. It involved observing 13 different pre-recorded CCTV clips of public space. The participants are provided with a clear written description of the targets they should find in each video. The study included a total of 24 participants with varying levels of experience in analyzing CCTV video. A Tobii eye tracking system was employed to record the eye movements of the participants. The data captured by the eye tracking sensor is analyzed using statistical data analysis approaches like SPSS and machine learning algorithms using WEKA. The research concluded the existence of differences in behavioural patterns which could be used to classify participants of study is appropriate machine learning algorithms are employed. The research conducted on video analytics was perceived to be limited to few iii projects where the human object being observed was viewed as one object, and hence the detailed analysis of human observer attention pattern based on human body part articulation has not been investigated. All previous attempts in human observer visual attention pattern analysis on CCTV video analytics and forensics either used conceptual or statistical approaches. These methods were limited with regards to making predictions and the detection of hidden patterns. A novel approach to articulating human objects to be identified and tracked in a visual surveillance task led to constrained results, which demanded the use of advanced machine learning algorithms for classification of participants The research conducted within the context of this thesis resulted in several practical data collection and analysis challenges during formal CCTV operator based surveillance tasks. These made it difficult to obtain the appropriate cooperation from the expert operators of CCTV for data collection. Therefore, if expert operators were employed in the study rather than novice operator, a more discriminative and accurate classification would have been achieved. Machine learning approaches like ensemble learning and tree based algorithms can be applied in cases where a more detailed analysis of the human behaviour is needed. Traditional machine learning approaches are challenged by recent advances in the field of convolutional neural networks and deep learning. Therefore, future research can replace the traditional machine learning approaches employed in this study, with convolutional neural networks. The current research was limited to 13 different videos with different descriptions given to the participants for identifying and tracking different individuals. The research can be expanded to include any complicated demands with regards to changes in the analysis process.

Existen actualmente muchas herramientas de administración de desarrollo de software, las cuales tienen elementos de Planificación y Tracking. Pero no muchas de ellas toman estos dos elementos y los combinan. Una de las herramientas que más hace hincapié en este último tema, es Painless Tracking, la cual es usada actualmente en el curso de CC61A. Esta herramienta está construida sobre una planilla Excel, que la hace no colaborativa y caracterizándola por tener serios problemas de usabilidad. A raíz de estos problemas y por experiencias personales, nace la idea, y objetivo de esta memoria, de diseñar e implementar la interfaz de usuario de la herramienta Painless Tracking versión WEB de manera de hacerla usable: colaborativa, fácil de usar, motivadora en su uso y aportando un mayor valor del que tiene actualmente. Para el desarrollo de esta aplicación se adaptará una metodología de ingeniería de software existente que consiste en usabilidad ágil. Es decir, utiliza metodologías ágiles de desarrollo pero tomando mucho en consideración la usabilidad del sistema final. El software obtenido está construido en una plataforma Web, la cual está orientada a una rápida interacción con el usuario, tratando de brindar mayor valor con el menor esfuerzo. Éste, está validado por usuarios finales, los cuales participaron en dos sesiones de pruebas de usuario, los cuales evaluaron positivamente el producto final. Gracias a las pruebas de usuario y a la metodología de trabajo se pudo obtener un producto que aporta mucho más valor que la versión original, como por ejemplo, mayor visibilidad, mejor interacción, mayor entendimiento de los elementos, mayor rapidez de uso y mayor feedback. Este producto está listo para ser utilizado por los alumnos del siguiente semestre de CC61A, en donde se espera que siga creciendo según el uso que le den éstos.

An image processing approach to turbulence studies has been developed. The approach employs a structure tracking technique to quantify the movement of coherent, large-scale turbulent structures. The 'structure tracking' technique has been applied to the shear layer of a low speed jet issuing into a low speed crossflow. A study of the characteristics of the turbulent flow within this region involved comparative measurements with hot-wire anemometry measurements within the same flow regime and fractal analysis of the flow visualisation images used by the tracking routine. Fractal analysis was applied to flow visualisation images to educe a range of length scales made apparent by the flow visualisation equipment The results obtained with the structure tracking technique included the instantaneous velocity of the structures and a measure of their length scales. The instantaneous velocity measurements were used to calculate a turbulence characteristic associated with the structures. Further analysis revealed subsets of this turbulence characteristic involving the variation in average velocity of individual structures as well as variations in the instantaneous velocity of individual structures. Where possible, the results of the structure tracking technique were compared to those achieved by hot wire anemometry and good correspondence was found between the mean flow characteristics measured by both techniques. The results of the two techniques began to diverge in the regions of the flow where conventional hot-wire anemometry was unable to discriminate between the flow associated with the jet and that associated with the crossflow. In such regions, time-averaged hot-wire anemometry produced results which combined the measurements in both flow regimes and therefore attenuated any characteristics of the jet which were significantly different from those of the crossflow. In the same flow regions the structure tracking technique was able to measure those characteristics specifically associated with the jet, producing results, which reflected the behaviour of the jet more accurately.

The Cash in Transit (CIT) industry demands reliable and innovative products from its suppliers to ensure safety and reliability within the industry. Product innovation has been directed at a bespoke tracking system for the Cash in Transit industry, which can meet its stringent requirements and excel above the capabilities of standard, readily available tracking systems. The presented research has investigated the state of the art in tracking and localisation systems and has highlighted Wi-Fi as a potential novel Cash in Transit tracking solution. With research into 2.4GHz Wi-Fi and the effects in a CIT environment, the technology has been understood and demonstrated in terms of its advantages and weaknesses when applied to CIT. The research has shown that 2.4GHz Wi-Fi is a novel and viable solution for both wide area tracking and localised tracking of a Cash in Transit security box by testing innovative ways of detecting theft using 2.4GHz Wi-Fi in a set of specific real-world scenarios. An embedded tracking system was developed and a thorough evaluation undertaken using a series of practical usage scenarios. The results show the proposed tracking capability is very effective and ready for initial effective use within a Cash in Transit security box.

Product designers address the costs of assembly during the design process. Design process can be more efficient if assembly issues could be addressed early in its design process. Doing this requires the ability to assess assemblability among others. Assemblability refers to the ease of assembling the final product from its parts. Assemblability evaluation is applied by product designers for quantitatively estimating the degree of difficulty of the assembly. This helps in identifying areas of improvement, so as to reduce process time and production costs. This work focuses on assessing assemblability in a manual assembly and its importance in the earlier phases of design. Literature contains various methods for assessing assemblability (e.g. Boothroyd-Dewhurst method, the DFA house, Sturges DFA calculator and Sony DFA method). These methods are typically rule-based and their use requires insight and knowledge on the part of the designer. Further, the designer has to interpret and apply them differently in each specific and unique case. Literature also contains methods for ergonomic assessment of manual work and its link with assemblability. Both observation based ergonomic assessment such as RULA, REBA, VIDAR, LUBA and OWAS and instrumentation based ergonomic assessment using electro-goniometer and accelerometer are the techniques reviewed in this thesis for their suitability in assembly assessment. The most recent trend in the area is automation of the evaluation process. This thesis proposes an approach to automated assessment of assemblability using electromagnetic trackers. In spite of advances in industrial automation, manual assembly tasks continue to be an important feature of many industrial operations. The method proposed in the thesis is for the assessment of assemblability of manual assembly that combines both time and postural analysis. The tool used for the static analysis is called Rapid Upper Limb Assessment (RULA); for dynamic analysis a new method of time analysis is proposed that is based on the ratio of time spent in fine and gross motions carried out in an assembly process. The difficulty of assembly of a series of manual assembly tasks are carried out in a laboratory setting. Then by correlating this assessment with the feedback on the difficulty of these assembly task obtained from the subjects who carried out these tasks. The remaining work carried out as a part of this thesis is focussed on automating the process of carrying out the above assessment in an automated manner. Suitability of electromagnetic trackers as a means for automated capture of data necessary for executing the proposed assessment method is studied. Electromagnetic trackers have been used to capture postural data for various limbs of the assembly operators. Data from the limbs are then analysed to identify, to which limb movement signifies which sources of difficulty (i.e. reach, visibility, etc.) in assembly; for example reach difficulty is indicated by torso movement. Finally, the thesis proposes as a part of the future work in possible improvement of the assessment method. Also, its application using a virtual reality (VR) platform assesses in ascertaining ease or difficulties in assembly and many.

La recherche présentée ici constitue l’une des applications du projet de recherche « InterHumain », et son objectif principal est double : développer les connaissances dont on dispose actuellement sur le fonctionnement de l’interaction en général ; et, décrire avec plus de précision les capacités interactionnelles des schizophrènes dans le but de contribuer à l’élaboration de techniques de prise en charge adaptées à leurs troubles cognitifs. Afin de concevoir un modèle de l’interaction plurimodal, nous avons analysé des interactions en face à face entre un expérimentateur (psychologue) et un schizophrène. Cela nous a amené à comparer certaines propriétés des compétences interactionnelles des sujets « normaux » à celles des sujets schizophrènes afin d’identifier les capacités et les difficultés qu’ils manifestent au niveau du langage et des mouvements oculaires. Nous centrons les analyses dans ce manuscrit sur deux aspects de l’interaction : la séquentialité du discours et les saccades oculaires. Ce modèle sera éprouvé au moyen du système faceLAB5. Il s’agit d’un système d’enregistrement et de suivi des mouvements oculaires (« eye-tracking ») que nous avons doublé afin d’obtenir des données sur les deux interlocuteurs en situation d’interaction. De plus, les résultats seront mis en perspective avec les données issues de bilans neuropsychologiques afin, notamment, de déterminer le rôle que pourrait jouer le lobe frontal dans le maintien de l’interaction. Les principaux résultats sont en accord avec ceux issus de nombreuses études antérieures utilisant un seul système d’ « eye-tracking » antérieures, notamment que les patients schizophrènes produisent plus de mouvements de saccades oculaires que les participants témoins. Mais le dispositif, tel que nous l’avons conçu, permet également l’analyse du fonctionnement de l’interlocuteur donc de l’expérimentateur. Celui-ci manifeste une baisse de sa production de saccades oculaires lorsqu’il est en interaction avec les patients schizophrènes. De plus, les résultats aux tests neuropsychologiques montrent que malgré certaines déficiences déjà identifiées chez les patients schizophrènes, certaines capacités cognitives semblent préservées. Cette observation pourraient être le point d’ancrage d’une restauration des capacités cognitives actuellement en déclins voir déficitaires chez certains patients schizophrènes, par la mise au point de thérapies spécifiques et adaptées. Cela leur permettrait d’exploiter au mieux toutes leurs capacités cognitives, soit au quotidien, soit en vue d’une insertion sociale et professionnelle à long terme. / The research presented here is one of the application of the research project “inter-human” and it has a twofold objective: to develop the knowledge currently available on the functioning of the interaction in general; and to describe more accurately interactional skills of schizophrenic patients in order to contribute to the development of care techniques appropriate to their cognitive disorders. In order to design a model of multimodal interaction, we analyzed face to face interactions between an experimenter (psychologist) and a schizophrenic patient. This led us to compare some properties of interactional skills of “normal” subjects to those of schizophrenic patients in order to identify the capabilities and challenges they manifest via language and eye movements. In this thesis, we focus the analyzes on two aspects of interaction: sequentiality of speech and saccadic eye movements. This model will be tested using the faceLAB5 system. This system is a recording and monitoring system of eye movements ("eye-tracking") that we doubled to get data on both parties in a situation of interaction. In addition, the results will be put into perspective with data taken from neuropsychological evaluations, in order to identify the possible role of the frontal lobe in maintaining the interaction. The main results are consistent with those from many other studies that used an earlier single “eye-tracking” system, in particular that schizophrenic patients produce more saccadic eye movements than “normal” participants. But designed as it was, the device also allows the analysis of the behavior of the interlocutor, that is to say the experimenter. This shows a decrease in production of saccadic eye movements from the experimenter when interacting with schizophrenic patients. In addition, the results on neuropsychological tests show that despite some disabilities already identified in schizophrenic patients, some cognitive abilities seem to be preserved.This observation could be the cornerstone of the restoration of cognitive capacities that are declining or are deficient in some schizophrenia patients, by the development of specific and appropriate therapies. This would allow them to exploit all their cognitive abilities, either daily or in a view to a social and professional long term integration.

Global Positioning Systems (GPS) is undergoing stunning changes and upgrades which will enhance the Civil and Military users. This modernization included new satellite signals for Civil and Military purposes which benefits the fundamental signal acquisition and tracking of the GPS receiver. These new signals enable a new family of alternatives for mitigating the ionospheric errors that currently limit the GPS accuracy [16]. A new Civil signal L2 Civil (L2C) was commissioned on the L2 frequency which could have ionospheric error elimination capability, with better cross correlation, Data recovery performance, and threshold tracking. The complex structure of the signal calls for new Acquisition approaches which are implementable with limited computational burden. This thesis proposes an Acquisition methodology to acquire the Code phase offset and Carrier frequency offset of the L2C signal which can be implemented in real time. The algorithm employs a serial code search for Code Phase by retaining the original sampling frequency `fs' and implements a FFT search for carrier frequency offset with a reduced sampling frequency of `fs/M' where `M' is the decimation rate. Multirate Filters are employed for reducing the sampling frequency. After the Acquisition is performed, the values are passed onto the Phase Lock Loop (PLL) and Delay Lock Loop (DLL) to further synchronize the Code Phase and Carrier frequency. The algorithm was tested on a real data set for the performance evaluation of Acquisition and Tracking, and the navigation bits were extracted and the results discussed.

This thesis aims to address some of the deficiencies that exist in this discipline, in order to widen the applicability of biotelemetry methods and ultimately provide new data which will improve our understanding of animal movement strategies.