A Unified Taxonomy and Multimodal Dataset for Events in Invasion Games

Official repository for the paper:

Biermann, H., Theiner, J., Bassek, M., Raabe, D., Memmert, D., & Ewerth, R. (2021, October). A Unified Taxonomy and Multimodal Dataset for Events in Invasion Games. In Proceedings of the 4th International Workshop on Multimedia Content Analysis in Sports (pp. 1-10).

Contents

• Events in Invasion Games Dataset - Handball (EIGD-H)
  • Data Source & Characteristics
  • License
  • Download
  • Visualization Positional Data
• Events in Invasion Games Dataset - Soccer (EIGD-S)
• Human Performance Evaluation
• Annotation Guidelines and Event Definitions
• Citation

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Events in Invasion Games Dataset - Handball (EIGD-H)

This dataset contains the broadcast video streams of handball matches along with synchronized official positional data and human event annotations for 125min raw data in summary.

Data Source & Characteristics

• Handball matches from the Handball-Bundesliga (HBL) captured in saison 2019/20
• Size: 5 matches x 5 sequences x 5min
• Video:
  • unedited broadcast video stream (no cuts, no overlays)
  • HD resolution (1280x720px)@30fps
• Positional data:
  • official captured by Kinexon
  • manually synchronized to video streams (offsets and sampling rate (originally captured at 20Hz))
• Events:
  • frame-wise annotations based solely on the video content
  • annotations according to the proposed taxonomy
  • multiple annotations for two matches (10 sequences) from 3 experts
  • hierarchical event format: <root_event>.<sub_event>.<sub_sub_event>
  • statistics: [event_statistics.ipynb]

License

Position and video data are provided by Kinexon with authorization of the Handball-Bundesliga (HBL). As EIGD-H is licensed under CC BY-NC-SA 4.0 you must give appropriate credit when using this dataset by

1. naming the Handball-Bundesliga (HBL)
2. citing this publication

Download

You can download the annotations, position and video data manually at https://data.uni-hannover.de/dataset/eigd or automatically using download_eigd.sh:

Visualization Positional Data

See visualize_positional_data.ipynb

Events in Invasion Games Dataset - Soccer (EIGD-S)

Annotations and URLs to the videos are available at https://data.uni-hannover.de/dataset/eigd .

• Videos are captured from the official FIFA youtube channel
• Size: 5 matches x 5 sequences x 5min
• Video:
  • edited broadcast video stream
  • HD resolution (1280x720px)@25fps
• Events:
  • frame-wise annotations based solely on the video content
  • annotations according to the proposed taxonomy
  • multiple annotations for two matches (10 sequences) from 4 experts and one inexperienced annotator
  • hierarchical event format: <root_event>.<sub_event>.<sub_sub_event>

Human Performance Evaluation

To measure the aggreement of multiple annotators, i.e. the expected human performance, you can use these two notebooks (evaluate_eigd-h.ipynb and evaluate_eigd-s.ipynb) to reproduce the results of the paper. The formatted output is also accessbile here.

Annotation Guidelines and Event Definitions

See definitions.md and examples.md.

Citation

@inproceedings{BiermannTaxonomyMMSports21,
author = {Biermann, Henrik and Theiner, Jonas and Bassek, Manuel and Raabe, Dominik and Memmert, Daniel and Ewerth, Ralph},
title = {A Unified Taxonomy and Multimodal Dataset for Events in Invasion Games},
year = {2021},
isbn = {9781450386708},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3475722.3482792},
doi = {10.1145/3475722.3482792},
booktitle = {Proceedings of the 4th International Workshop on Multimedia Content Analysis in Sports},
pages = {1–10},
numpages = {10},
keywords = {event detection, human performance analysis, datasets, events in sports},
location = {Virtual Event, China},
series = {MMSports'21}
}