Projects per year
Abstract
This paper presents a transformer encoder-decoder model for predicting future badminton strokes based on previous rally actions. The model uses court position skeleton poses and player-specific embeddings to learn stroke and player-specific latent representations in a spatiotemporal encoder module. The representations are then used to condition the subsequent strokes in a decoder module through rally-aware fusion blocks which provide additional relevant strategic and technical considerations to make more informed predictions. RallyTemPose shows improved forecasting accuracy compared to traditional sequential methods on two real-world badminton datasets. The performance boost can also be attributed to the inclusion of improved stroke embeddings extracted from the latent representation of a pre-trained large-language model subjected to detailed text descriptions of stroke descriptions. In the discussion the latent representations learned by the encoder module show useful properties regarding player analysis and comparisons.
Original language | English |
---|---|
Title of host publication | Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops |
Publication date | Jun 2024 |
Pages | 3376-3385 |
Publication status | Published - Jun 2024 |
Event | CVPR 2024 - The IEEE/CVF Conference on Computer Vision and Pattern Recognition - Seattle Convention Center, Seattle, United States Duration: 17 Jun 2024 → 21 Jun 2024 Conference number: 2024 https://cvpr.thecvf.com/ |
Conference
Conference | CVPR 2024 - The IEEE/CVF Conference on Computer Vision and Pattern Recognition |
---|---|
Number | 2024 |
Location | Seattle Convention Center |
Country/Territory | United States |
City | Seattle |
Period | 17/06/2024 → 21/06/2024 |
Internet address |
Keywords
- badminton
- transformer
Fingerprint
Dive into the research topics of 'A stroke of genius: Predicting the next move in badminton'. Together they form a unique fingerprint.Projects
- 1 Finished
-
TeamSPORTek: Team Danmark – Dansk Sports Teknologi Forsknings Netværk
Hansen, D. W. (PI) & Grasshof, S. (CoI)
01/09/2020 → 31/12/2024
Project: Research