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Variational Object-aware 3D Hand Pose from a Single RGB Image

VO-handpose

The implementation of our paper accepted in IROS 2019 - jointly presented in IEEE Robotics and Automation Letters

Authors: Yafei Gao, Yida Wang, Nassir Navab and Federico Tombari

Dataset

This dataset provides 11020 samples. Each sample provides:

  • RGB image (320x320 pixels);
  • Segmentation mask (320x320 pixels) for hand
  • Segmentation mask (320x320 pixels) for object
  • 21 Keypoints for hand with their uv coordinates in the image frame and their xyz coordinates in the camera coordinate system
  • Intrinsic Camera Matrix

It was created with freely accessible character from MakeHuman and rendered with Blender

Introduction

The dataset ships with minimal examples, that browse the dataset and show samples. There is one example for Phython and one for MATLAB users, both functionalities are identical. Both files are located in the root folder.

Download

You can find download.py from here, then run it under your data folder:

python download.py -o ./<DATA FOLDER>/

File structures

./ 			: Root folder
./color			: Color images
./mask_hand		: Segmentation masks for hand
./mask_object		: Segmentation masks for object
./annotation.mat	: Key point annotations and camera matrices

If you find this work useful in your research, please cite:

@article{gao2019variational,
  title={Variational Object-Aware 3-D Hand Pose From a Single RGB Image},
  author={Gao, Yafei and Wang, Yida and Falco, Pietro and Navab, Nassir and Tombari, Federico},
  journal={IEEE Robotics and Automation Letters},
  volume={4},
  number={4},
  pages={4239--4246},
  year={2019},
  publisher={IEEE}
}

Contact

Converning questions regarding to our dataset, please contact Yafei Gao ([email protected])