Due to growing security concerns, video surveillance and monitoring has received an immense attention from both federal agencies and private firms. The main concern is that a single camera, even if allowed to rotate or translate, is not sufficient to cover a large area for video surveillance. A more general solution with wide range of applications is to allow the deployed cameras to have a non-overlapping field of view (FoV) and to, if possible, allow these cameras to move freely in 3D space. This thesis addresses the issue of how cameras in such a network can be calibrated and how the network as a whole can be calibrated, such that each camera as a unit in the network is aware of its orientation with respect to all the other cameras in the network. Different types of cameras might be present in a multiple camera network and novel techniques are presented for efficient calibration of these cameras. Specifically: (i) For a stationary camera, we derive new constraints on the Image of the Absolute Conic (IAC). These new constraints are shown to be intrinsic to IAC; (ii) For a scene where object shadows are cast on a ground plane, we track the shadows on the ground plane cast by at least two unknown stationary points, and utilize the tracked shadow positions to compute the horizon line and hence compute the camera intrinsic and extrinsic parameters; (iii) A novel solution to a scenario where a camera is observing pedestrians is presented. The uniqueness of formulation lies in recognizing two harmonic homologies present in the geometry obtained by observing pedestrians; (iv) For a freely moving camera, a novel practical method is proposed for its self-calibration which even allows it to change its internal parameters by zooming; and (v) due to the increased application of the pan-tilt-zoom (PTZ) cameras, a technique is presented that uses only two images to estimate five camera parameters. For an automatically configurable multi-camera network, having non-overlapping field of view and possibly containing moving cameras, a practical framework is proposed that determines the geometry of such a dynamic camera network. It is shown that only one automatically computed vanishing point and a line lying on any plane orthogonal to the vertical direction is sufficient to infer the geometry of a dynamic network. Our method generalizes previous work which considers restricted camera motions. Using minimal assumptions, we are able to successfully demonstrate promising results on synthetic as well as on real data. Applications to path modeling, GPS coordinate estimation, and configuring mixed-reality environment are explored.

<div> <p>According to self-determination theory (SDT), the extent to which students’ motivation is self-determined is critical for their academic performance. When self-determined, students learn because of personal interest or identification, out of a sense of volition, as opposed to pressure or indifference. SDT also proposes that self-determined academic motivation is facilitated when the learning environment supports the basic psychological needs for autonomy, relatedness, and competence. This model of social support à needs satisfaction à motivation à learning outcomes is termed the general self-determination theory model (hereafter the General Model), and numerous studies have provided support for it. </p> <p>However, the current evidence regarding the General Model is limited, in that no study to date has examined it in its full using within-individual methods. Between-individual analytical methods answer the question of whether a person with higher response on variable A is also more likely to report higher levels of B, whereas within-individual analytical methods answer the question of whether the same person is more likely to experience variable B when reporting experiences of A. Despite the popularity of between-individual methods in educational psychology, they may not be able to reveal the within-person relationships between variables, which are critical for understanding inner psychological processes and mechanisms. </p> <p>Therefore, the current study aims to apply a within-individual analytical approach to the General Model, using a large dataset collected at Purdue over several years. Specifically, in the current dataset, not only may a student provide multiple responses, but also the same classroom contain various students’ responses. Therefore, a cross-classified path model is used, such that the General Model is analyzed under the framework of “responses cross-classified under students and classrooms”. This model enables me to explain the variance-covariance matrix of the variables using the General Model on three levels: the situational (within-student and within-classroom) level, the student level, and the classroom level.</p> <p>Results generally supported the predictions of the General Model on the within-individual, within-classroom level. That is, for the same student, in the same classroom, when she or he experiences higher levels of autonomy support, they would also be more likely to have their psychological needs satisfied, and to study for self-determined reasons, which is then associated with higher perceived learning performance. Unexpected findings include the dominant effect of competence, the direct effects of learning climate and competence, and the lack of relationship between grades and other variables. The General Model is also largely replicated on the student- and classroom-levels.</p> <p>In addition, supplemental analyses showed that (1) although the general trend of motivation and perceived learning climate across one’s college life is null, the trend is moderated by major, such that students in business-related majors decrease in self-determined motivation and perceptions of autonomy support, whereas students in social sciences increase in self-determined motivation and perceptions of autonomy support; (2) there is limited and inconsistent support for a buffer effect, such that the higher autonomy and competence needs satisfaction students generally get, the lower their needs satisfaction in a specific classroom depends on the learning climate. Overall, the current research provides a comprehensive and multilevel understanding of the role of self-determination in the classroom.</p></div>

Current literature lacks longitudinal understandings of the association between childhood sexual/physical violence, alcohol use, depressive symptoms, and indiscriminant sexual behaviors among young women, as well as the racial/ethnic differences in these associations. Therefore, using the 1994-2008 National Longitudinal Study of Adolescent Health, this study examined a) heterogeneous growth trajectories of problem alcohol use during the transition from adolescents to young adulthood and the impact of childhood sexual/physical violence on drinking trajectories, b) the long-term impact of childhood sexual/physical violence on alcohol use and depressive symptoms, and c) the structural associations between childhood sexual/physical violence and indiscriminant sexual behaviors by examining alcohol use and depressive symptoms as mediators between White and African-American women. First, with 1,702 women, LCGM was used to identify trajectories of problem alcohol use using the first three waves. Four trajectories of problem alcohol use emerged: stable abstainers; decliners (moderate-low); incliners (low-moderate); and rapid incliners (low-high). From the bivariate level analyses, in reference to stable abstainers, White women who experienced childhood sexual/physical violence were more likely to be rapid incliners (low-high). Second, with 1,756 women, autoregressive cross-lagged path models were performed to test longitudinal associations between childhood sexual/physical violence, problem alcohol use, and depressive symptoms of White and African-American women. Both groups demonstrated significant association between childhood sexual/physical violence and subsequent development of depressive symptoms, while only White women demonstrated significant association with subsequent problem alcohol use. Third, with 1,388 women, SEM and multigroup SEM were used to test pathways between childhood sexual/physical violence and indiscriminant sexual behaviors for White and African-American women. SEM indicates that problem alcohol use and depressive symptoms mediated the proposed relationship. Multigroup SEM indicates that, for White women, both problem alcohol use and depressive symptoms mediated the association between childhood sexual/physical violence and indiscriminant sexual behaviors, while only depressive symptoms mediated the proposed association for African-American women. These findings highlight the importance of designing and providing effective prevention and treatment programs for women who experienced childhood sexual/physical violence to interrupt subsequent problem alcohol use, depressive symptoms, and indiscriminant sexual behaviors. / text

En Analyse Sensorielle, les préférences des consommateurs sont généralement modélisées en fonction de données sensorielles par les méthodes de cartographie des préférences. L'objectif de cette thèse est de modéliser les préférences des consommateurs en intégrant, en plus des données sensorielles, de nouvelles variables relatives à leur perception des produits. Nous appellerons ces variables les dimensions subjectives. Elles recouvrent des dimensions pragmatiques liées à l'utilisation du produit et des dimensions plus symboliques telles que l'esthétisme, la modernité, l'originalité…Les problématiques relatives aux dimensions subjectives ont d'abord été étudiées lors d'une étude exploratoire sur des tasses à café. L'ensemble du travail a ensuite été réalisé sur 11 sièges de voitures. Dans un premier temps, des entretiens qualitatifs ont été réalisés auprès de 16 consommateurs d'une part et de 2 designers d'autre part. Ces entretiens ont permis d'identifier les dimensions subjectives caractéristiques des sièges. Une évaluation quantitative des dimensions subjectives et des préférences a ensuite été réalisée par 110 consommateurs. Enfin, les sièges ont été caractérisés sensoriellement par des experts. Les préférences des consommateurs ont été modélisées en fonction des données sensorielles et des dimensions subjectives par des modèles d'équations structurelles à variables latentes, plus précisément par Partial Least Square Path Modeling. Quatre modèles, fondés sur les groupes de préférences, ont été mis en place. Selon le groupe étudié, la contribution des deux jeux de données diffère et quatre profils de clients sont identifiés. D'un point de vue méthodologique, ce travail fournit des éléments de réponse sur l'intérêt des dimensions subjectives pour la modélisation des préférences. L'ensemble de la démarche est en cours d'application sur un produit alimentaire : le chocolat. / In Sensory Science, preference mapping is used to explain consumers' preferences with sensory data. This PhD aims to integrate not only sensory data but also new variables that are related to consumers' perception of the product in the modelling of consumers' preferences. These variables are labelled as subjective dimensions. They address the pragmatic dimensions that cover the context of use of the products and more symbolic dimensions, such as aesthetics, modernity, originality…An exploratory study based on coffee cups was a first mean to approach the issues related to subjective dimensions. Then, all the work was done on a study of 11 car seats. The first step consisted in qualitative interviews of 16 consumers and of 2 designers. These interviews allowed identifying the subjective dimensions that characterize car seats. 110 consumers then performed a quantitative evaluation of their preferences and subjective dimensions. Finally, the seats were characterized by experts with sensory descriptors. The consumers' preferences were modelled according to both sensory data and subjective dimensions, using structural equations: the Partial Least Square Path Modeling. Four models based on preferences clustering were established. The contribution of two kinds of data differed according to the considered cluster, which led to the identification of four customer profiles. From a methodological point of view, this work provides first elements about the benefit of subjective dimensions in preference modelling. The methodology is being implemented on a food product: chocolate.

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