Two stream network for stroke detection in table tennis

Zahra, Anam; Martin, Pierre-Etienne

doi:10.48550/arXiv.2112.12073

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Conference Paper

Two stream network for stroke detection in table tennis

MPS-Authors

/persons/resource/persons272101

Zahra, Anam
Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;

/persons/resource/persons266715

Martin, Pierre-Etienne
Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

Zahra_Two_MediaEval_2021.pdf
(Any fulltext), 666KB

Supplementary Material (public)

There is no public supplementary material available

Citation

Zahra, A., & Martin, P.-E. (2021). Two stream network for stroke detection in table tennis. In Proceedings of MediaEval 2021: Multimedia Benchmark Workshop. doi:10.48550/arXiv.2112.12073.

Cite as: https://hdl.handle.net/21.11116/0000-000A-4B11-F

Abstract

This paper presents a table tennis stroke detection method from videos. The
method relies on a two-stream Convolutional Neural Network processing in
parallel the RGB Stream and its computed optical flow. The method has been
developed as part of the MediaEval 2021 benchmark for the Sport task. Our
contribution did not outperform the provided baseline on the test set but has
performed the best among the other participants with regard to the mAP metric.