Open Thesis
Ongoing Thesis
Master's Theses
Hand Pose Estimation Using Multi-View RGB-D Sequences
Keywords:
Hand Object Interaction, Pose Estimation, Deep Learning
Hand Object Interaction, Pose Estimation, Deep Learning
Description
In this project the task is to fit a parametric hand mesh model and a set of rigid objects to a sequence of multi-view RGB-D cameras. Existing models for hand key-point detection and 6DoF pose estimation for rigid objects models have significantly evolved in recent years. Our goal is to utilize such models to estimate the hand and object poses.
Related Work
- https://dex-ycb.github.io/
- https://www.tugraz.at/institute/icg/research/team-lepetit/research-projects/hand-object-3d-pose-annotation/
- https://github.com/hassony2/obman
- https://github.com/ylabbe/cosypose
Prerequisites
- Knowledge in computer vision.
- Experience about segmentation models (i.e. Detectron2)
- Experience with deep learning frameworks PyTorch or TensorFlow(2.x).
- Experience with Pytorch3D is a plus.
Contact
marsil.zakour@tum.de
Supervisor:
Marsil Zakour