Sökning: "Object pose estimation"
Visar resultat 1 - 5 av 27 uppsatser innehållade orden Object pose estimation.
1. MISK-Moves
Kandidat-uppsats, Lunds universitet/Certec - Rehabiliteringsteknik och DesignSammanfattning : Move-to-play is a musical instrument for persons with both cognitive and physical impairments, who would have trouble playing traditional instruments. Everyone, no matter their abilities, are given the chance to play and control music by moving their own body. LÄS MER
2. Analyzing different approaches to Visual SLAM in dynamic environments : A comparative study with focus on strengths and weaknesses
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Simultaneous Localization and Mapping (SLAM) is the crucial ability for many autonomous systems to operate in unknown environments. In recent years SLAM development has focused on achieving robustness regarding the challenges the field still faces e.g. dynamic environments. LÄS MER
3. Research and Application of 6D Pose Estimation for Mobile 3D Cameras
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This work addresses the deep-learning-based 6 Degree-of-Freedom (DoF) pose estimation utilizing 3D cameras on an iPhone 13 Pro. The task of pose estimation is to estimate the spatial rotation and translation of an object given its 2D or 3D images. LÄS MER
4. Deep Learning for estimation of fingertip location in 3-dimensional point clouds : An investigation of deep learning models for estimating fingertips in a 3D point cloud and its predictive uncertainty
Master-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : Sensor technology is rapidly developing and, consequently, the generation of point cloud data is constantly increasing. Since the recent release of PointNet, it is possible to process this unordered 3-dimensional data directly in a neural network. LÄS MER
5. Generating 3D Scenes From Single RGB Images in Real-Time Using Neural Networks
Kandidat-uppsats, Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)Sammanfattning : The ability to reconstruct 3D scenes of environments is of great interest in a number of fields such as autonomous driving, surveillance, and virtual reality. However, traditional methods often rely on multiple cameras or sensor-based depth measurements to accurately reconstruct 3D scenes. LÄS MER