# CPFES: Physical Fitness Evaluation Based on Canadian Agility and Movement Skill Assessment

arXiv: https://arxiv.org/abs/2308.14324 · HTML: https://mlsanity.com/paper/2308.14324/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 24 references that are in the map.
- First posted on arXiv 28 Aug 2023.

## Builds on (most cited first, 10 of 10)

- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015)
- [Fast R-CNN](https://mlsanity.com/paper/1504.08083/) (2015)
- [Rich feature hierarchies for accurate object detection and semantic segmentation](https://mlsanity.com/paper/1311.2524/) (2013)
- [YOLO9000: Better, Faster, Stronger](https://mlsanity.com/paper/1612.08242/) (2016)
- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [BlazePose: On-device Real-time Body Pose tracking](https://mlsanity.com/paper/2006.10204/) (2020)
- [Combining detection and tracking for human pose estimation in videos](https://mlsanity.com/paper/2003.13743/) (2020)
- [PoseTrack: Joint Multi-Person Pose Estimation and Tracking](https://mlsanity.com/paper/1611.07727/) (2016)
- [Multi-person Articulated Tracking with Spatial and Temporal Embeddings](https://mlsanity.com/paper/1903.09214/) (2019)

## Abstract (arXiv)

In recent years, the assessment of fundamental movement skills integrated with physical education has focused on both teaching practice and the feasibility of assessment. The object of assessment has shifted from multiple ages to subdivided ages, while the content of assessment has changed from complex and time-consuming to concise and efficient. Therefore, we apply deep learning to physical fitness evaluation, we propose a system based on the Canadian Agility and Movement Skill Assessment (CAMSA) Physical Fitness Evaluation System (CPFES), which evaluates children's physical fitness based on CAMSA, and gives recommendations based on the scores obtained by CPFES to help children grow. We have designed a landmark detection module and a pose estimation module, and we have also designed a pose evaluation module for the CAMSA criteria that can effectively evaluate the actions of the child being tested. Our experimental results demonstrate the high accuracy of the proposed system.