Sökning: "3D Reconstruction"

Visar resultat 1 - 5 av 195 uppsatser innehållade orden 3D Reconstruction.

  1. 1. Using NeRF- and Mesh-Based Methods to Improve Visualisation of Point Clouds

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Vilma Ylvén; Oscar Montelin; [2024]
    Nyckelord :Technology and Engineering; Mathematics and Statistics;

    Sammanfattning : 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

  3. 2. Replacing Objects in Point Cloud stream with Real-time Meshes using Semantic Segmentation

    Master-uppsats, Blekinge Tekniska Högskola

    Författare :Abhinav Chitta; [2024]
    Nyckelord :;

    Sammanfattning : 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. 3. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Erica Ingerstad; Liv Kåreborn; [2024]
    Nyckelord :NeRF; Neural Radiance Field; Satellite Imagery; Machine Learning; Deep Learning;

    Sammanfattning : 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. 4. Using Neural Radiance Fields and Gaussian Splatting for 3D reconstruction of aircraft inspections

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Roos Eline Bottema; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : 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

  7. 5. Assessing the Efficiency of COLMAP, DROID-SLAM, and NeRF-SLAM in 3D Road Scene Reconstruction

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marcus Ascard; Farjam Movahedi; [2023]
    Nyckelord :3D reconstruction; Visual SLAM; Pose evaluation; Point cloud evaluation; Road scenes; Technology and Engineering;

    Sammanfattning : 3D reconstruction is a field in computer vision which has evolved rapidly as a result of the recent advancements in deep learning. As 3D reconstruction pipelines now can run in real-time, this has opened up new possibilities for teams developing Advanced Driver Assistance Systems (ADAS), which rely on the camera system of the vehicle to enhance the safety and driving experience. LÄS MER