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 58 for “"Depth Estimation"”.
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Unsupervised monocular depth estimation: Learning to generalize
Models for unsupervised monocular depth estimation (MDE) have gained much attention due to recent breakthroughs and the ability to train with unlabeled data. Despite the state-of-the-art methods performing well on depth prediction benchmarks, certain artifacts and their performance compared to …
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Using Texture Features To Perform Depth Estimation
… need in real world applications for estimating depth through electronic means without human intervention. There are many methods in the field which help in autonomously finding depth measurements. Some of which are using LiDAR, Radar, etc. One of the most researched topic in the field of depth …
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Multiview monocular depth estimation using unsupervised learning methods
Existing learned methods for monocular depth estimation use only a single view of scene for depth evaluation, so they inherently overt to their training scenes and cannot generalize well to new datasets. This thesis presents a neural network for multiview monocular depth estimation. Teaching a …
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Depth estimation from 3D reconstructed scene using stereo vision
… robots to do their job efficiently. Distance estimation is one of these applications that a lot of researches made to develop it. Visionary sensors such as stereo vision optimization method is one of the most efficient methods among traditional sensors that have been used to estimate a depth …
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Consistent Depth Estimation in Data-Driven Simulation for Autonomous Driving
In this work we propose consistent depth estimation for viewpoint reconstruction in data-driven simulation, combining aspects of learning-based monocular depth prediction and structure-from-motion to increase temporal video depth accuracy. We demonstrate efficacy in VISTA, an end-to-end autonomous …
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Dataset and Evaluation of Self-Supervised Learning for Panoramic Depth Estimation
<p>Depth detection is a very common computer vision problem. It shows up primarily in robotics, automation, or 3D visualization domains, as it is essential for converting images to point clouds. One of the poster child applications is self driving cars. Currently, the best methods for depth …
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Generic camera calibration for omnifocus imaging, depth estimation and a train monitoring system
… to new algorithms in omnifocus imaging, 3D scene depth from focus and machine vision based intermodal freight train analysis. In the first prat of this dissertation, we present new progress made in the areas of camera calibration with application to omnifocus imaging and 3D scene depth from focus …
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Self-supervised Learning of Monocular Depth from Video
Image-based depth estimation as a fundamental problem in computer vision allows for understanding the scene geometry using only cameras. This thesis addresses the specific problem of monocular depth estimation via self-supervised learning from RGB-only videos. Although existing work has shown …
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Algorithms for single-view depth image estimation
Depth sensing is fundamental in autonomous navigation, localization, and mapping. However, existing depth sensors offer many shortcomings, especially low effective spatial resolutions. In order to attain enhanced resolution with existing hardware, this dissertation studies the single-view depth …
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Software Tools for Integral Imaging Virtual Studios
… computer generation of virtual scenes, object depth estimation of the real scenes, and compositing of the real and virtual scenes. On computer generation of integral images, a set of computational models is systematically investigated and particularly three types of imaging schemes are derived. …
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Efficient Ensemble-based Bayesian Neural Networks for Depth Regression
Depth estimation is a computer vision task that involves the estimation of distance to objects based on provided images and plays a crucial role in a wide variety of applications, such as autonomous driving. In many application areas, the decisions of Neural Networks (NNs) are safety-critical and …
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Programmable Aperture Photography: An investigation into applications and methods
… various applications such as defocus deblurring, depth estimation and light field acquisition. Traditional coded aperture masks are constructed from static materials such as cardboard and cannot be altered once their shapes have been defined. These masks are then physically inserted into the …
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Real-time Topology-Aware Augmented Reality
… deep learning-based framework for monocular depth estimation, which learns non-Euclidean features and improves the accuracy of depth estimations. Mathematical background on group equivariance, including translation equivariance and permutation equivariance, is also introduced to provide …
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Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network
Depth estimation is one of the most important problems in computer vision. It has attracted a lot of attention because it has applications in many areas, such as robotics, VR and AR, self-driving cars etc. Using the defocus blur of a camera lens is one of the methods of depth estimation. In this …
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Planejamento de redes pluviométricas
… the design of network aiming total areal storm depth estimation, one considering implicit and the other explicity the configuration are discussed. These two approaches are applied to the Rio de Janeiro city rainfall network.
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Light field applications to 3-dimensional surface imaging
… may be captured to produce light fields. Simple depth estimation algorithms using stereo and focus measures are then applied to recover quantitative depth information. Experiments on real-world light fields demonstrate their utility in performing digital refocusing, reconstructing occluded …
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Photon-limited time of flight depth acquisition : new parametric model and its analysis
As 3-D imaging systems become more popular, the depth estimation which is their core component should be made as accurate as possible at low power levels. In this thesis, we consider the time of flight depth acquisition problem at low photon counts. We first formulate the received light intensity …
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Implementation of stereo correspondence algorithms for multi-baseline vision system
… varying camera baselines on correspondence and depth estimation. As the baseline increases the resolution of depth increases but finding correspondences is very tedious. On the other hand when cameras are placed close to each other and thereby reducing the baseline distance points in the images …
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SMARTGUIDE: Revolutionizing the Depth and Dependability of Vision-Impaired Navigation
… combining QR code detection via YOLO with ZoeDepth for depth estimation, guiding users to destinations through the shortest path calculated by Dijkstra's algorithm; and (3) Obstacle Detection and Alerts, where YOLO identifies obstacles, and ZoeDepth estimates their distance to inform users of …
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