Sökning: "3D Vision"

Visar resultat 1 - 5 av 223 uppsatser innehållade orden 3D Vision.

  1. 1. 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

  3. 2. The State of Live Facial Puppetry in Online Entertainment

    Magister-uppsats, Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakulteten

    Författare :Lisa Gren; Denny Lindberg; [2024]
    Nyckelord :Facial Puppetry; Face Tracking; Real-time Rendering; Motion Capture; Computer Vision; 3D Modeling; Virtual Avatars; Augmented Reality; Machine Learning; Game Development;

    Sammanfattning : Avatars are used more and more in online communication, in both games and socialmedia. At the same time technology for facial puppetry, where expressions of the user aretransferred to the avatar, has developed rapidly. LÄS MER

  4. 3. 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

  5. 4. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Kobe Moerman; [2023]
    Nyckelord :3D pose estimation; Joint landmarks; Variational autoencoder; Multi-task model; Loss discrimination; Latent-space modulation; Depth map; 3D-positionsuppskattning; Gemensamma landmärken; Variationell autoencoder; Multitask-modell; Förlustdiskriminering; Latent-space-modulering; Djupkarta;

    Sammanfattning : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. 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