Global ETD Search

71	Reconstruction robuste des vaisseaux sanguins pour les simulations médicales interactives à partir de données patients Yureidini, Ahmed 13 May 2014 (has links) (PDF) Dans le cadre des simulations interactives, le manque de modèles géométriques reste une des limitations majeures des simulateurs. Actuellement, les simulateurs commerciaux ne proposent pas ou un tout cas, un nombre limité de cas. Un grand nombre des travaux abordent cependant ce sujet tout au long de ces deux dernières décennies. Malgré une vaste littérature, les méthodes ne sont pas adaptées à un contexte interactif, plus particulièrement quand il s'agit des réseaux vasculaires. Dans cette thèse, nous considérons le problème de la segmentation et la reconstruction des vaisseaux sanguins à partir de données patients en Angiographie Rotationnelle (RA) 3D. Pour ce faire, nous proposons deux nouveaux algorithmes, un pour la segmentation et un autre, pour la reconstruction. Tout d'abord, le réseau vasculaire est construit grâce à un algorithme de suivi de la ligne centrale des vaisseaux. De plus, notre procédure de suivi extrait des points à la surface des vaisseaux de manière robuste. Deuxièmement, ces points sont estimés par une surface implicite (un blobby model) qui est, à son tour, raffinée de façon itérative. Les résultats du suivi et de la reconstruction sont produit à partir de données synthétiques et réelles. Lors de la simulation de la navigation d'outils interventionnels, notre modèle géométrique remplit les exigences des simulations interactives: une prédiction et détection rapide des collisions, l'accès à l'information topologique, une surface lisse et la mise à disposition de quantités différentielles pour la résolution des contacts. Simulations médicales interactives Segmentation Suivi des vaisseaux sanguins Estimation de cylindre RANSAC Blobby models
72	Modern Stereo Correspondence Algorithms : Investigation and Evaluation Olofsson, Anders January 2010 (has links) Many different approaches have been taken towards solving the stereo correspondence problem and great progress has been made within the field during the last decade. This is mainly thanks to newly evolved global optimization techniques and better ways to compute pixel dissimilarity between views. The most successful algorithms are based on approaches that explicitly model smoothness assumptions made about the physical world, with image segmentation and plane fitting being two frequently used techniques. Within the project, a survey of state of the art stereo algorithms was conducted and the theory behind them is explained. Techniques found interesting were implemented for experimental trials and an algorithm aiming to achieve state of the art performance was implemented and evaluated. For several cases, state of the art performance was reached. To keep down the computational complexity, an algorithm relying on local winner-take-all optimization, image segmentation and plane fitting was compared against minimizing a global energy function formulated on pixel level. Experiments show that the local approach in several cases can match the global approach, but that problems sometimes arise – especially when large areas that lack texture are present. Such problematic areas are better handled by the explicit modeling of smoothness in global energy minimization. Lastly, disparity estimation for image sequences was explored and some ideas on how to use temporal information were implemented and tried. The ideas mainly relied on motion detection to determine parts that are static in a sequence of frames. Stereo correspondence for sequences is a rather new research field, and there is still a lot of work to be made. stereo correspondence stereo matching cost function cost aggregation image segmentation plane fitting RANSAC graph cuts belief propagation disparity depth estimation Övrig annan teknik Computational Mathematics Beräkningsmatematik
73	Analýza vlastností stereokamery ZED ve venkovním prostředí / Analysis of ZED stereocamera in outdoor environment Svoboda, Ondřej January 2019 (has links) The Master thesis is focused on analyzing stereo camera ZED in the outdoor environment. There is compared ZEDfu visual odometry with commonly used methods like GPS or wheel odometry. Moreover, the thesis includes analyses of SLAM in the changeable outdoor environment, too. The simultaneous mapping and localization in RTAB-Map were processed separately with SIFT and BRISK descriptors. The aim of this master thesis is to analyze the behaviour ZED camera in the outdoor environment for future implementation in mobile robotics.
74	Uniform Marker Field na válci / Uniform Marker Field on a Cylinder Kříž, Radim January 2013 (has links) This work presents a new extension for Uniform Marker Field, which is able to detect UMF on the cylinder. First part of the text deals with Augmented reality and focuses on systems using markers. It discusses the actual state-of-the-art systems and its possibilities. After that it focuses more deeply on the marker system Uniform marker field and its grayscale variants. Next part of the work describes properties of the cylinder projected in real space. Important properties for detecting are discussed in detail. Then the proposal and description of detection algorithm is presented. Implementation of algorithm is tested and evaluated on the very end of this thesis.
75	Vyhledávání graffiti tagů podle podobnosti / Graffiti Tag Retrieval Grünseisen, Vojtěch January 2013 (has links) This work focuses on a possibility of using current computer vision alghoritms and methods for automatic similarity matching of so called graffiti tags. Those are such graffiti, that are used as a fast and simple signature of their authors. The process of development and implementation of CBIR system, which is created for this task, is described. For the purposes of finding images similarity, local features are used, most notably self-similarity features.
76	Zlepšení rozlišení pro vícečetné snímky stejné scény / Superresolution Mezera, Lukáš January 2010 (has links) Úkolem této diplomové práce je navrhnout vlastní metodu pro zvýšení rozlišení v obraze scény, pokud je k dispozici více snímků dané scény. V teoretické části diplomové práce jsou jako nejlepší metody pro zvýšení rozlišení v obraze vybrány ty, které jsou založeny na principech zpracování signálu. Dále jsou popsány základní požadavky metod pro zvýšení rozlišení v obraze při přítomnosti více snímků stejné scény a jejich typická struktura. Následuje stručný přehled těchto metod a jejich vzájemné porovnání podle optimálních kritérií. Praktická část diplomové práce se zabývá samotným návrhem metody pro zvýšení rozlišení v obraze, pokud je k dispozici více snímků této scény. První navržená metoda je naimplementována a otestována. Při testování této metody je však zjištěna její špatná funkčnost pro snímky scény s nízkým rozlišením, které vznikly vzájemnou rotací. Z toho důvodu je navržena vylepšená metoda pro zvýšení rozlišení v obraze. Tato metoda využívá při svém výpočtu robustních technik. Díky tomu je již vylepšená metoda nezávislá na rotaci mezi snímky scény s nízkým rozlišením. I tato metoda je řádně otestována a její výsledky jsou porovnány s výsledky první navržené metody pro zvýšení rozlišení v obraze. V porovnání výpočetních časů je lepší první navrhovaná metoda, avšak její výsledky pro obrazy obsahující rotace nejsou kvalitní. Oproti tomu pro obrazy, které vznikly pouze posunem při snímání scény, jsou tyto výsledky velice dobré. Vylepšená metoda je tedy využitelná zejména pro obrazy obsahující rotace. V závěru této práce je ještě navrženo jedno vylepšení, které by mohlo zlepšit výsledky druhé navrhnuté metody pro zvýšení rozlišení v obraze scény.
77	Generation and Optimization of Local Shape Descriptors for Point Matching in 3-D Surfaces Taati, BABAK 01 September 2009 (has links) We formulate Local Shape Descriptor selection for model-based object recognition in range data as an optimization problem and offer a platform that facilitates a solution. The goal of object recognition is to identify and localize objects of interest in an image. Recognition is often performed in three phases: point matching, where correspondences are established between points on the 3-D surfaces of the models and the range image; hypothesis generation, where rough alignments are found between the image and the visible models; and pose refinement, where the accuracy of the initial alignments is improved. The overall efficiency and reliability of a recognition system is highly influenced by the effectiveness of the point matching phase. Local Shape Descriptors are used for establishing point correspondences by way of encapsulating local shape, such that similarity between two descriptors indicates geometric similarity between their respective neighbourhoods. We present a generalized platform for constructing local shape descriptors that subsumes a large class of existing methods and allows for tuning descriptors to the geometry of specific models and to sensor characteristics. Our descriptors, termed as Variable-Dimensional Local Shape Descriptors, are constructed as multivariate observations of several local properties and are represented as histograms. The optimal set of properties, which maximizes the performance of a recognition system, depend on the geometry of the objects of interest and the noise characteristics of range image acquisition devices and is selected through pre-processing the models and sample training images. Experimental analysis confirms the superiority of optimized descriptors over generic ones in recognition tasks in LIDAR and dense stereo range images. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2009-09-01 11:07:32.084 computer vision range data object recognition tracking local shape descriptor point matching pose estimation pose acquisition 3-D 3D point cloud satellite tracking optimization range image processing range image RANSAC registration alignment surface computational geometry detection localization model-based object identification point correspondence feature selection VD-LSD LSD genetic algorithm simulated annealing forward feature selection multivariate features subset selection local properties LIDAR dense stereo stereo precision feature matching machine learning training learning phase preprocessing

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