Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 20 for “"Graph cuts"”.
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Image and video segmentation using graph cuts
Includes abstract. Includes bibliographical references (leaves 67-71).
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A pixel-parallel architecture for graph cuts inference
… re- quires efficient algorithms. The method of graph cuts converts a maximum a posteriori (MAP) inference problem on Markov random fields (MRFs) into a network flow, which can be solved in a direct manner. Many computer vision problems can be conveniently cast as an inference task to find a most …
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Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network
… this purpose. In this research, we have applied graph cuts and convolutional neural network (DfD-net) to estimate depth from defocus blur using a natural (Middlebury) and a virtual (Maya) dataset. Graph Cuts showed similar performance for both natural and virtual datasets in terms of NMAE and …
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Approximate inference methods for grid-structured MRFs
… compared the mean field, belief propagation, and graph cuts methods for performing approximate inference on an MRF. I developed a method by which the memory requirements for belief propagation could be significantly reduced. I also developed a modification of the graph cuts algorithm that allows …
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Shape Estimation Using Graph Cut
… optimization problems which are solved using graph cut. Particularly, an approach called graph cuts based active contours (GCBAC) is proposed, and its applications to 2D object segmentation and three-dimensional (3D) object modeling are discussed. In the application of object segmentation, the …
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Improve OpenMVG and create a novel algorithm for novel view synthesis from point clouds
… Random Field (MRF) optimization problem using graph-cuts. We introduce a novel energy minimization formulation exploits both 2D and 3D information. Finally, a photorealistic image of the novel view is rendered by copying pixel colors from selected candidate source images using pixel labels …
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Geometric and Photometric Modeling of Three-Dimensional Scenes From Multiple Views
… we take an object-centered matching approach. Graph cuts on surface distance grid are used to robustly reconstruction 3D shape based on a non-Lambertian photo consistency measure. Then, the texture, illumination and geometric refinement are estimated based on a bilinear reflection equation that …
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Early Vision Optimization: Parametric Models, Parallelization and Curvature
… Thirdly, fast methods for finding minimal graph cuts and solving related problems on modern parallel hardware are developed and extensively evaluated. Finally, the thesis is concluded with two applications to early vision problems: heart segmentation and image registration.
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Joint estimation of water and fat images from magnetic resonance signals
… complication, optimization algorithms based on graph cuts have been developed and studied. Additionally, this work addresses the modeling issues of fat-water separation by comparing a set of recently proposed models, demonstrating that accurate spectral modeling of the acquired signal is …
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Efficient Machine Learning with High Order and Combinatorial Structures
… otherwise difficult to use within the standard graphical modeling framework. For each potential, we develop associated algorithms so that the type of interaction can be used efficiently in a variety of settings. We further show that this HOP toolbox is useful not only for defining models, but …
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Multi-view image refocusing
… is a potential research area in computer graphics and computer vision. By definition it means focusing an image again, or changing the emphasized region in a given image. To achieve the focusing job, it requires shallow depth of field to create a focus-defocus scene, which depends on …
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Image Based View Synthesis
… expanded and outliers are rejected employing the graph cuts method integrated with level set representation. Next, these initial regions are merged into several initial layers according to the motion similarity. Third, the occlusion order constraints on multiple frames are explored, which …
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Multi-stage processing for effective segmentation of SAR sea ice images
… proposed for the established algorithm, Kernel Graph Cuts (KGC), for acquiring further improved segmentation results. The post processing incorporates algorithms such as Skeletonisation, Morphology and Active Contours. The proposed algorithm is compared against existing techniques such as the …
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Multi-Level Learning Approaches for Medical Image Understanding and Computer-aided Detection and Diagnosis
… is evaluated on a large-scale chest radiograph view identification task and a multi-class radiograph annotation task, demonstrating its improved performance in comparison with other state-of-the-art algorithms. It also achieves high accuracy and robustness against images with severe …
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Structured support vector machines learning and application in computer vision
… explicitly enforcing the submodular condition, graph cuts is conveniently integrated as the inference engine to attain the optimal label assignment efficiently. Our approach allows learning a model with thousands of parameters, which is further facilitated by parallel computation in the learning …
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Structured support vector machines learning and application in computer vision
… explicitly enforcing the submodular condition, graph cuts is conveniently integrated as the inference engine to attain the optimal label assignment efficiently. Our approach allows learning a model with thousands of parameters, which is further facilitated by parallel computation in the learning …
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Projection methods for clustering and semi-supervised classification
… on a different approach to clustering based on graph cuts. The minimum normalised graph cut objective has gained considerable attention as relaxations of the objective have been developed, which make them solvable for reasonably well sized problems. This has been adopted by the highly popular …
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Predicting object occupancy on the floor from RGBD images of indoor scenes
This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be used in the field of robotics where robots need to navigate through a room while …
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Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring
<p>More complex image understanding algorithms are increasingly practical in a host of emerging applications. Object tracking has value in surveillance and data farming; and object recognition has applications in surveillance, data management, and industrial automation. In this work we introduce an …