SARA Dataset

Synthetic dataset used for model training in the IEEE Access paper "A Body Part Embedding Model With Datasets for Measuring Human Motion Similarity in 2D". See project page for more details.

Prerequisites

• Python 3
• Numpy

Downloading and Preprocessing the SARA

• Download and extract the SARA dataset (Google drive)

• Clone this repository

• Preprocess the dataset (performs motions split into fixed frames)

  python preprocess.py /path/to/the/extracted/

• The directory structure after preprocessing :

   SARA_released
   |-- test
   |-- train
   `-- |-- Character_ID
       `-- |-- Motion_ID
           `-- |-- The number of frames
               `-- |-- Motion variations
                   |   |-- motion.npy (full-frame motion)
                   `-- |-- motions
                       |-- |-- 1.npy (fixed-frame motion)
                       |-- |-- 2.npy
                       |-- |-- ...
  

Example of Data Path

train/FuseFemaleA/Adventure3/100/Height_1|Activity_-1

FuseFemaleA : Character Id. Each character has different body structure.

Adventure3 : Motion category + ID.

100 : Motion frame length. Even the same motion can vary in length depending on the variation characteristics.

Height_1|Activity_-1 : The Height characteristic has a value of 1, and the Activity characteristic has a value of -1. Values range from -1 to 1.

Citation

If you use this dataset for your research, please cite the paper:

@ARTICLE{9366759,
  author={J. {Park} and S. {Cho} and D. {Kim} and O. {Bailo} and H. {Park} and S. {Hong} and J. {Park}},
  journal={IEEE Access}, 
  title={A Body Part Embedding Model With Datasets for Measuring 2D Human Motion Similarity}, 
  year={2021},
  volume={9},
  number={},
  pages={36547-36558},
  doi={10.1109/ACCESS.2021.3063302}}