Global ETD Search

11	Color-Based Fingertip Tracking Using Modified Dynamic Model Particle Filtering Method Zhu, Ting 27 July 2011 (has links) No description available. Electrical Engineering Fingertip Tracking Particle Filtering High-order Priori Motion Model Finger Mouse
12	Návrh systému Auto Taxi pro letoun / Auto Taxi System Design for Aircraft Kardoš, Juraj January 2015 (has links) Nedávné studie předpovídají nárůst pasažérů využívajících leteckou dopravu. Tento trend bude vyžadovat zavedení nových leteckých linek, důsledkem čeho bude zhuštěn letový provoz s dopadem hlavně na nápor letišť v metropolitních oblastech. Automatizovaně řízení pojíždení letounu umožní menší rozestupy mezi jednotlivými linkami a zvýšení příletové a odletové kapacity letišť. Tato práce se zabývá návrhem modelu pohybu dopravního letounu po zemi s ohledem na různé provozní podmínky jako např.: stav povrchu vzletové a přistávací dráhy za různého počasí a lišící se provozní parametry letounu (tlak v pneumatikách, zatížení podvozků a pod.). Validace modelu byla založena na sledování poloměru zatáčky pro různe uhly natočení přední podvozkové nohy. Výsledky simulace byly validovany vzhledem k analytickému modelu Ackermanovy geometrie a na specifikační dokument od Boeingu určený pro plánovaní pohybu letounu na letišti. Výsledky prokázaly přesnost modelu a potvrdily jeho možné nasazení pro simulace v reálnem čase.
13	Generalized Area Tracking Using Complex Discrete Wavelet Transform: The Complex Wavelet Tracker Yilmaz, Sener 01 July 2007 (has links) (PDF) In this work, a new method is proposed that can be used for area tracking. This method is based on the Complex Discrete Wavelet Transform (CDWT) developed by Magarey and Kingsbury. The CDWT has its advantages over the traditional Discrete Wavelet Transform such as approximate shift invariance, improved directional selectivity, and robustness to noise and illumination changes. The proposed method is a generalization of the CDWT based motion estimation method developed by Magarey and Kingsbury. The Complex Wavelet Tracker extends the original method to estimate the true motion of regions according to a parametric motion model. In this way, rotation, scaling, and shear type of motions can be handled in addition to pure translation. Simulations have been performed on the proposed method including both quantitative and qualitative tests. Quantitative tests are performed on synthetically created test sequences and results have been compared to true data. The performance is compared with intensity-based methods. Qualitative tests are performed on real sequences and evaluations are presented empirically. The results are compared with intensity-based methods. It is observed that the proposed method is very accurate in handling affine deformations for long term sequences and is robust to different target signatures and illumination changes. The accuracy of the proposed method is compatible with intensity-based methods. In addition to this, it can handle a wider range of cases and is robust to illuminaton changes compared to intensity-based methods. The method can be implemented in real-time and could be a powerful replacement of current area trackers.
14	ESTIMATING THE RESPIRATORY LUNG MOTION MODEL USING TENSOR DECOMPOSITION ON DISPLACEMENT VECTOR FIELD Kang, Kingston 01 January 2018 (has links) Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation. With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a model to formulate the motion through a mathematical function over time. [Li et al., 2011] uses principal component analysis (PCA) to propose one such model using each image as a long vector. However, the images come in a multidimensional arrays, and vectorization breaks the spatial structure. Driven by the needs to develop low-rank tensor decomposition and provided the 4DCT and Displacement Vector Field (DVF), we introduce two tensor decompositions, Population Value Decomposition (PVD) and Population Tucker Decomposition (PTD), to estimate the respiratory lung motion with high levels of accuracy and data compression. The first algorithm is a generalization of PVD [Crainiceanu et al., 2011] to higher order tensor. The second algorithm generalizes the concept of PVD using Tucker decomposition. Both algorithms are tested on clinical and phantom DVFs. New metrics for measuring the model performance are developed in our research. Results of the two new algorithms are compared to the result of the PCA algorithm. Displacement Vector Field Tensor Decomposition Population Value Decomposition Population Tucker Decomposition Low-rank Approximation Lung Respiratory Motion Model Biostatistics Oncology Radiology Statistical Methodology Statistical Models Theory and Algorithms
15	Object Detection in Dynamic Background / Détection d’objets dans un fond dynamique Ali, Imtiaz 05 March 2012 (has links) La détection et la reconnaissance d’objets dans des vidéos numériques est l’un des principaux challenges dans de nombreuses applications de vidéo surveillance. Dans le cadre de cette thèse, nous nous sommes attaqué au problème difficile de la segmentation d’objets dans des vidéos dont le fond est en mouvement permanent. Il s’agit de situations qui se produisent par exemple lorsque l’on filme des cours d’eau, ou le ciel,ou encore une scène contenant de la fumée, de la pluie, etc. Il s’agit d’un sujet assez peu étudié dans la littérature car très souvent les scènes traitées sont plutôt statiques et seules quelques parties bougent, telles que les feuillages par exemple, ou les seuls mouvements sont des changements de luminosité. La principale difficulté dans le cadre des scènes dont le fond est en mouvement est de différencier le mouvement de l’objet du mouvement du fond qui peuvent parfois être très similaires. En effet, par exemple, un objet dans une rivière peut se déplacer à la même allure que l’eau. Les algorithmes de la littérature extrayant des champs de déplacement échouent alors et ceux basés sur des modélisations de fond génèrent de très nombreuses erreurs. C’est donc dans ce cadre compliqué que nous avons tenté d’apporter des solutions.La segmentation d’objets pouvant se baser sur différents critères : couleur, texture,forme, mouvement, nous avons proposé différentes méthodes prenant en compte un ou plusieurs de ces critères.Dans un premier temps, nous avons travaillé dans un contexte bien précis qui était celui de la détection des bois morts dans des rivières. Ce problème nous a été apporté par des géographes avec qui nous avons collaboré dans le cadre du projet DADEC (Détection Automatique de Débris pour l’Aide à l’Etude des Crues). Dans ce cadre, nous avons proposé deux méthodes l’une dite " naïve " basée sur la couleur des objets à détecter et sur leur mouvement et l’autre, basée sur une approche probabiliste mettant en oeuvre une modélisation de la couleur de l’objet et également basée sur leur déplacement. Nous avons proposé une méthode pour le comptage des bois morts en utilisant les résultats des segmentations.Dans un deuxième temps, supposant la connaissance a priori du mouvement des objets,dans un contexte quelconque, nous avons proposé un modèle de mouvement de l’objet et avons montré que la prise en compte de cet a priori de mouvement permettait d’améliorer nettement les résultats des segmentations obtenus par les principaux algorithmes de modélisation de fond que l’on trouve dans la littérature.Enfin, dans un troisième temps, en s’inspirant de méthodes utilisées pour caractériser des textures 2D, nous avons proposé un modèle de fond basé sur une approche fréquentielle.Plus précisément, le modèle prend en compte non seulement le voisinage spatial d’un pixel mais également le voisinage temporel de ce dernier. Nous avons appliqué la transformée de Fourier locale au voisinage spatiotemporel d’un pixel pour construire un modèle de fond.Nous avons appliqué nos méthodes sur plusieurs vidéos, notamment les vidéos du projet DADEC, les vidéos de la base DynTex, des vidéos synthétiques et des vidéos que nous avons faites. / Moving object detection is one of the main challenges in many video monitoring applications.In this thesis, we address the difficult problem that consists in object segmentation when background moves permanently. Such situations occur when the background contains water flow, smoke or flames, snowfall, rainfall etc. Object detection in moving background was not studied much in the literature so far. Video backgrounds studied in the literature are often composed of static scenes or only contain a small portion of moving regions (for example, fluttering leaves or brightness changes). The main difficulty when we study such situations is to differentiate the objects movements and the background movements that may be almost similar. For example, an object in river moves at the same speed as water. Therefore, motion-based techniques of the literature, relying on displacements vectors in the scene, may fail to discriminate objects from the background, thus generating a lot of false detections. In this complex context, we propose some solutions for object detection.Object segmentation can be based on different criteria including color, texture, shape and motion. We propose various methods taking into account one or more of these criteria.We first work on the specific context of wood detection in rivers. It is a part of DADEC project (Détection Automatique de Débris pour l’Aide à l’Etude des Crues) in collaboration with geographers. We propose two approaches for wood detection: a naïve method and the probabilistic image model. The naïve approach is based on binary decisions based on object color and motion, whereas the probabilistic image model uses wood intensity distribution with pixel motion. Such detection methods are used fortracking and counting pieces of wood in rivers.Secondly, we consider a context in which we suppose a priori knowledge about objectmotion is available. Hence, we propose to model and incorporate this knowledge into the detection process. We show that combining this prior motion knowledge with classical background model improves object detection rate.Finally, drawing our inspiration from methods used for 2D texture representation, we propose to model moving backgrounds using a frequency-based approach. More precisely, the model takes into account the spatial neighborhoods of pixels but also their temporal neighborhoods. We apply local Fourier transform on the obtained regions in order to extract spatiotemporal color patterns.We apply our methods on multiple videos, including river videos under DADEC project, image sequences from the DynTex video database, several synthetic videos andsome of our own made videos. We compare our object detection results with the existing methods for real and synthetic videos quantitatively as well as qualitatively Détection d’objets Segmentation Modèle de fond Modèle de mouvement Texture dynamique Transformée de Fourier locale Object detection Segmentation Background model Motion model Dynamic texture Local Fourier transform
16	Évolution des syndromes de pollinisation et des niches bioclimatiques au sein des genres antillais gesneria et rhytidophyllum (gesneriaceae) Alexandre, Hermine 04 1900 (has links) Contexte : Gesneria et Rhytidophyllum (Gesneriaceae) sont deux genres de plantes Antillais aillant subi une forte diversification et qui présentent une forte variabilité de modes de pollinisation associés à des traits floraux particuliers. Les spécialistes des colibris ont des fleurs tubulaires rouges, alors que les spécialistes des chauves-souris et les généralistes présentent des fleurs campanulées de couleur pâle. La capacité d’être pollinisé par des chauves-souris (en excluant les colibris ou en devenant généraliste) a évolué plusieurs fois indépendamment au sein du groupe. Ces caractéristiques font de ces plantes un bon modèle pour étudier les relations entre l’évolution des modes de pollinisation et la diversification spécifique et écologique. Pour ceci, nous avons étudié les bases génétiques des changements de mode de pollinisation et les liens entre ces modes de pollinisations et la diversification des niches bioclimatiques. Méthodes : Nous avons réalisé une étude de QTLs pour caractériser les régions génomiques associées à la transition de syndrome de pollinisation entre une espèce à stratégie de pollinisation mixte (Rhytidophyllum auriculatum) et une espèce spécialiste des colibris (Rhytidophyllum rupincola). Nous avons parallèlement analysé les relations entre les changements de modes de pollinisation (dimension biotique de la niche écologique) et l’évolution des niches bioclimatiques chez ces plantes. Enfin, d’un point de vue théorique, nous avons testé l’effet de la fréquence et de l’amplitude des changements environnementaux sur les patrons d’évolution des niches écologiques. Résultats : L’étude des QTLs a montré que la couleur et le volume de nectar sont basés chacun sur un QTL majeur, alors que la forme de la corolle a une base génétique plus complexe. Par ailleurs ces différents QTLs ne sont pas liés physiquement dans le génome. L’analyse des niches bioclimatiques a montré que ces Gesneriaceae antillaises sont caractérisées par un conservatisme phylogénétique de niche bioclimatique (PNC) et que l’évolution de ces niches est indépendante des stratégies de pollinisation. Les plantes semblent aussi être relativement généralistes du point de vue de leur niche abiotique. Finalement, nous avons testé l’hypothèse selon laquelle l’adaptation à un environnement temporellement hétérogène pourrait expliquer à la fois le caractère généraliste des plantes et leur patron de PNC. Cette hypothèse s’est trouvée partiellement vérifiée. Conclusion : Si l’indépendance génétique des traits floraux a pu faciliter l’émergence des syndromes de pollinisation en réduisant les contraintes génétiques, il semble que la répartition largement chevauchante des colibris et des chauves-souris ne représente pas une opportunité écologique suffisante pour expliquer les évolutions répétées vers la pollinisation par les chauves-souris. En revanche, les perturbations environnementales causant régulièrement des déclins dans les populations de pollinisateurs pourraient expliquer l’avantage des plantes qui ont une stratégie de pollinisation mixte. / Background: Gesneria and Rhytidophyllum (Gesneriaceae) are two genera endemic to the Antilles that underwent an important diversification and that present a great vari- ability in pollination modes with regard to specific floral traits. Hummingbird specialists harbour red tubular flowers while bat specialists and generalists have campanulate (i.e., bell shaped) flowers with pale colours. Bat pollination (excluding or not hummingbirds) evolved multiple times independently in this group. These plants are thus a good model to study the relationship between the evolution of pollination mode and ecological and species diversification. To understand these relationships, we studied the genetic basis of pollination mode transition and the link between pollination mode and bioclimatic niches diversification. Methods: We performed a QTL analysis to detect genomic regions underlying the floral traits involved in the pollination syndrome transition between Rhytidophyllum auriculatum (a generalist species) and Rhytidophyllum rupincola (a hummingbird specialist). Also, we analysed the consequence of pollination mode transitions (which represent the biotic part of ecological niches) on bioclimatic niches evolution in Gesneria and Rhytidophyllum. Then, we tested whether environmental changes can result in patterns of phylogenetic bioclimatic niche conservatism through time. Results: The QTLs analysis showed that corolla colour and nectar volume are both based on one major QTL, while corolla shape is determined by a more complex genetic architecture involving several unlinked QTLs. These Antillean Gesneriaceae were found to have a pattern of phylogenetic (bioclimatic) niche conservatism (PNC) and their niche evolution was found to be independent from pollination strategies. Overall, the plants were found to have relatively widespread bioclimatic niches. Finally, we partially confirmed the hypothesis that adapting to temporally variable environment might cause both species generalization and PNC pattern. Conclusion: Genetic independence of floral traits might have facilitated pollination syn- dromes evolution by reducing genetic constraints. However, the overlapping distribution of hummingbirds and bats do not represent an ecological opportunity that could explain re- peated evolutions toward bat pollination. However, environmental perturbations causing regular pollinator populations collapses could explain the advantage for plants to favour generalist strategies. Gesneria Rhytidophyllum syndromes de pollinisation niche bioclimatique QTL modèle de Brownian Motion Ornstein-Uhlenbeck variation environnementale pollination syndromes bioclimatic niche Brownian Motion model environmental variation
17	Path Planning for Unmanned Air and Ground Vehicles in Urban Environments Curtis, Andrew B. 05 February 2008 (has links) (PDF) Unmanned vehicle systems, specifically unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs), have become a popular research topic. This thesis discusses the potential of a UAV-UGV system used to track a human moving through complex urban terrain. This research focuses on path planning problems for both a UAV and a UGV, and presents effective solutions for both problems. In the UAV path planning problem, we desire to plan a path for a miniature fixed-wing UAV to fly through known urban terrain without colliding with any buildings. We present the Waypoint RRT (WRRT) algorithm, which accounts for UAV dynamics while planning a flyable, collision-free waypoint path for a UAV in urban terrain. Results show that this method is fast and robust, and is able to plan paths in difficult urban environments and other terrain maps as well. Simulation and hardware tests demonstrate that these paths are indeed flyable by a UAV. The UGV path planning problem focuses on planning a path to capture a moving target in an urban grid. We discuss using a target motion model based on Markov chains to predict future target locations. We then introduce the Capture and Propagate algorithm, which uses this target motion model to determine the probabilities of capturing the target in various numbers of steps and with various initial UGV moves. By applying some different cost functions, the result of this algorithm is used to choose an optimal first step for the UGV. Results demonstrate that this algorithm is at least as effective as planning a path directly to the current location of the target, and that in many cases, this algorithm performs better. We discuss these cases and verify them with simulation results. path planning urban terrain city UAV unmanned air vehicle trajectory tracking collision detection RRT waypoint UGV unmanned ground vehicle road graph motion graph Markov chain predictive motion model MAGICC Lab Electrical and Computer Engineering
18	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics
19	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics

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