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Skeleton Images Representation (SkeleMotion and TSRJI)

This repository holds the skeleton image representation codes for the papers

SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition, Carlos Caetano, Jessica Sena, François Brémond, Jefersson A. dos Santos, and William Robson Schwartz, AVSS 2019, Taipei, Taiwan.

[Arxiv Preprint]

Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference Joints, Carlos Caetano, François Brémond and William Robson Schwartz, SIBGRAPI 2019, Rio de Janeiro, Brazil.

[Arxiv Preprint]

Contents

• Usage Guide
  • Prerequisites
  • Code & Data Preparation
    • Get the code
    • Get the Skeleton Data
    • Usage
• Other Info
  • Citation
  • Contact

Usage Guide

Prerequisites

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The main dependencies to run the code are

• OpenCV
• NumPy

The codebase is written in Python 3.6. We recommend the Anaconda Python distribution.

Code & Data Preparation

Get the code

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Use git to clone this repository

git clone --recursive https://github.com/carloscaetano/skeleton-images

Get the Skeleton Data

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We experimented our skeleton images representation on two large-scale 3D action recognition datasets: NTURGB+D 60 and NTURGB+D 120. For more information about accessing the "NTU RGB+D" and "NTU RGB+D 120" datasets, go to ROSE website.

Usage

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To extract the skeleton images on NTU dataset, run the GenerateSkeletonImages.py. It has four arguments:

• [--data_path] Directory containing the NTU skeleton data
• [--img_type] Image type to compute:
  • 1 - CaetanoMagnitude (SkeleMotion - AVSS2019);
  • 2 - CaetanoOrientation (SkeleMotion - AVSS2019);
  • 3 - CaetanoTSRJI (TSRJI - SIBGRAPI2019)
• [--temp_dist] Temporal distance between frames
• [--path_to_save] Directory to save the extracted skeleton images

Example

To extract the Magnitude skeleton image, with temporal distance = 10, from the NTU dataset located in the directory ./nturgb+d_skeletons/ and save the skeleton images to the folder ./CaetanoMagnitude, you can run

python GenerateSkeletonImages.py --data_path ./nturgb+d_skeletons/ --img_type 1 --temp_dist 10 --path_to_save ./CaetanoMagnitude

Other Info

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Citation

Please cite the following papers if you feel this repository useful.

@inproceedings{Caetano:AVSS:2019,
  author    = {Carlos Caetano and
               Jessica Sena and
               François Brémond and
               Jefersson A. dos Santos and
               William Robson Schwartz},
  title     = {SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition},
  booktitle   = {IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS)},
  year      = {2019},
}

@inproceedings{Caetano:SIBGRAPI:2019,
  author    = {Carlos Caetano and
               François Brémond and
               William Robson Schwartz},
  title     = {Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference Joints},
  booktitle   = {Conference on Graphics, Patterns and Images (SIBGRAPI)},
  year      = {2019},
}

Contact

For any question, please contact

Carlos Caetano: carlos.caetano@dcc.ufmg.br