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Conference Paper
Lightweight 2D Human Pose Estimation for Fitness Coaching System
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- Authors
- Hobeom Jeon, Youngwoo Yoon, Dohyung Kim
- Issue Date
- 2021-06
- Citation
- International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2021, pp.1-4
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, we describe lightweight 2D human pose estimation for a fitness coaching system. To achieve real-time inference speed on mobile devices, we propose the online pose distillation learning strategy that trains large teacher networks and small student networks simultaneously. The proposed lightweight model requires significantly lower computation as well as shows competitive pose estimation accuracy on the COCO keypoint detection dataset. In addition, the model was fine-tuned on a fitness dataset for the fitness coaching application where various fitness postures were accessed.
- KSP Keywords
- Estimation accuracy, Human Pose estimation, Learning Strategy, Lightweight model, Mobile devices, Real-time inference, keypoint detection, teacher networks