Sökning: "3D Human Motion"

Visar resultat 1 - 5 av 41 uppsatser innehållade orden 3D Human Motion.

  1. 1. 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

  3. 2. Enhancing Long-Term Human Motion Forecasting using Quantization-based Modelling. : Integrating Attention and Correlation for 3D Motion Prediction

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

    Författare :Luis González Gudiño; [2023]
    Nyckelord :Human Motion Forecasting; Long-Term Prediction; VQ-VAE; Quantization; 3D Human Motion; CMU MoCap Dataset; Transformer; Mänsklig Rörelseprognos; Långsiktig Prognos; VQ-VAE; Kvantisering; 3D-mänsklig rörelse; CMU MoCap Dataset; Transformer;

    Sammanfattning : This thesis focuses on addressing the limitations of existing human motion prediction models by extending the prediction horizon to very long-term forecasts. The objective is to develop a model that achieves one of the best stable prediction horizons in the field, providing accurate predictions without significant error increase over time. LÄS MER

  4. 3. Exploring Normalizing Flow Modifications for Improved Model Expressivity

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

    Författare :Marcel Juschak; [2023]
    Nyckelord :Normalizing Flows; Motion Synthesis; Invertible Neural Networks; Glow; MoGlow; Maximum Likelihood Estimation; Generative models; normaliserande flöden; rörelsesyntes; inverterbara neurala nätverk; Glow; MoGlow; maximum likelihood-skattning generativa modeller;

    Sammanfattning : Normalizing flows represent a class of generative models that exhibit a number of attractive properties, but do not always achieve state-of-the-art performance when it comes to perceived naturalness of generated samples. To improve the quality of generated samples, this thesis examines methods to enhance the expressivity of discrete-time normalizing flow models and thus their ability to capture different aspects of the data. LÄS MER

  5. 4. Arbitrary motion Synthetic Aperture Radar

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Filip Alberius; Erik Rolander; [2023]
    Nyckelord :RADAR; SAR; Synthetic Aperture Radar; Pulsed Coherent Radar; PCR; VR; Virtual Reality; IMU; Inertial Measurment Unit; VAA; Virtual Antenna Array; Obstacle detection; Signal Processing; Matched Filter Method.; Technology and Engineering;

    Sammanfattning : Syftet med denna avhandling är att utveckla en ny metod för att producera bilder med syntetisk aperturradar (SAR), med utgångspunkt i scenarier med arbiträr rörelse vad gäller radarsensorn. SAR är en väletablerad metod för att skapa 2- eller 3-dimensionella radarbilder, som traditionellt sett antar att radar-sensorns rörelse är linjär och förutsägbar. LÄS MER

  7. 5. 3D Estimation of Joints for Motion Analysis in Sports Medicine : A study examining the possibility for monocular 3D estimation to be used as motion analysis for applications within sports with the goal to prevent injury and improve sport specific motion

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

    Författare :Axel Persson; [2023]
    Nyckelord :;

    Sammanfattning : 3D joint estimation can be used to track bodies in areas such as entertainment, sports, biomedicine and surveillance to identify bodies from video streams and images. This is most commonly done with multi-view solutions but researchers are currently spending a large amount of resources into developing mono-view solutions. LÄS MER