Sökning: "data reconstruction"
Visar resultat 1 - 5 av 447 uppsatser innehållade orden data reconstruction.
1. Using NeRF- and Mesh-Based Methods to Improve Visualisation of Point Clouds
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : In recent years, the field of generating synthetic images from novel view points has seen some major improvements. Most importantly with the publication of Neural Radiance Fields allowing for extremely detailed and accurate 3D novel views. LÄS MER
2. Utilizing Hydra for Real-Time Reconstruction of Environments in Extended Reality
Master-uppsats, Lunds universitet/Ergonomi och aerosolteknologiSammanfattning : This thesis explores the use of Hydra for real-time reconstruction of environments in extended reality (XR). The development of the prototype was performed in an iterative manner. Three iterations were executed, each resulting in a prototype with improvements related to the takeaways from the preceding prototype. LÄS MER
3. Replacing Objects in Point Cloud stream with Real-time Meshes using Semantic Segmentation
Master-uppsats, Blekinge Tekniska HögskolaSammanfattning : Background: The evolving landscape of 3D data processing, particularly pointcloud manipulation, is pivotal in numerous applications ranging from architecturaldesign to spatial analysis. Traditional methods, primarily mesh generation from point clouds, face challenges in adapting to complex real-world scenarios. LÄS MER
4. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments
Master-uppsats, Linköpings universitet/DatorseendeSammanfattning : This thesis investigates the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, per- forms in predicting seasonal variations across different months. LÄS MER
5. Using Neural Radiance Fields and Gaussian Splatting for 3D reconstruction of aircraft inspections
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : The rapid evolution of machine learning techniques has revolutionized computer vision, particularly with the introduction of Neural Radiance Fields (NeRF) and the optimization of 3D Gaussians for rendering novel scene views. These methods, such as NeRF and Gaussian Splatting, have demonstrated success in synthetic data scenarios with consistent lighting and well-captured scenes. LÄS MER