# A New Perspective for Shuttlecock Hitting Event Detection

arXiv: https://arxiv.org/abs/2306.10293 · HTML: https://mlsanity.com/paper/2306.10293/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 11 references that are in the map.
- First posted on arXiv 17 Jun 2023.

## Builds on (most cited first, 5 of 5)

- [Searching for MobileNetV3](https://mlsanity.com/paper/1905.02244/) (2019)
- [Temporal Convolutional Networks for Action Segmentation and Detection](https://mlsanity.com/paper/1611.05267/) (2016)
- [TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios](https://mlsanity.com/paper/2108.11539/) (2021)
- [GolfDB: A Video Database for Golf Swing Sequencing](https://mlsanity.com/paper/1903.06528/) (2019)
- [CoachAI: A Project for Microscopic Badminton Match Data Collection and Tactical Analysis](https://mlsanity.com/paper/1907.12888/) (2019)

## Abstract (arXiv)

This article introduces a novel approach to shuttlecock hitting event detection. Instead of depending on generic methods, we capture the hitting action of players by reasoning over a sequence of images. To learn the features of hitting events in a video clip, we specifically utilize a deep learning model known as SwingNet. This model is designed to capture the relevant characteristics and patterns associated with the act of hitting in badminton. By training SwingNet on the provided video clips, we aim to enable the model to accurately recognize and identify the instances of hitting events based on their distinctive features. Furthermore, we apply the specific video processing technique to extract the prior features from the video, which significantly reduces the learning difficulty for the model. The proposed method not only provides an intuitive and user-friendly approach but also presents a fresh perspective on the task of detecting badminton hitting events. The source code will be available at https://github.com/TW-yuhsi/A-New-Perspective-for-Shuttlecock-Hitting-Event-Detection.