Sökning: "Motion Capturing"

Visar resultat 1 - 5 av 41 uppsatser innehållade orden Motion Capturing.

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. Event-Based Visual SLAM : An Explorative Approach

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

   Författare :Johan Rideg; [2023]
   Nyckelord :event camera; neuromorphic; SLAM; visual odometry;

   Sammanfattning : Simultaneous Localization And Mapping (SLAM) is an important topic within the field of roboticsaiming to localize an agent in a unknown or partially known environment while simultaneouslymapping the environment. The ability to perform robust SLAM is especially important inhazardous environments such as natural disasters, firefighting and space exploration wherehuman exploration may be too dangerous or impractical. LÄS MER

4. 3. 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

5. 4. Geometric Brownian Motion Option Pricing Model for Professional Football Contracts

   C-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

   Författare :Dennis Markovic; Emil Schough; [2023]
   Nyckelord :Geometric Brownian motion; Football; Investment analysis; Real options;

   Sammanfattning : In recent years, the valuation of football players has gained significant attention, especially in the context of their transfer value in the market. Our investigation explores the application of a Geometric Brownian Motion option pricing model to estimate the transfer value of football players, considering the option-like characteristics of player contracts. LÄS MER

7. 5. Beyond Traditional Tomography: X-ray Multi-projection Imaging for Additive Manufacturing

   Kandidat-uppsats, Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionen

   Författare :Maria Esther Vilar Alvarez; [2023]
   Nyckelord :X-ray tomography; X-ray multiprojection-imaging; deep learning; additive manufacturing; synchrotron radiation; Physics and Astronomy;

   Sammanfattning : The main aim of this bachelor thesis is to push the limits of 3D X-ray imaging by studying the minimum number of projections required to retrieve high-quality reconstructions for additive manufacturing processes. This project first focuses on understanding how X-ray tomography works, by reconstructing additive manufacturing data already obtained (from PSI, TOMCAT beamline) using two standard reconstruction algorithms, GRIDREC and SIRT. LÄS MER