Developed posture correction and rep-counting solutions using OpenPifPaf, quantized for TensorRT mobile edge devices.
This pose detection system helps users maintain proper form during exercises, reducing injury risk and maximizing workout effectiveness.
Leveraging OpenPifPaf's powerful pose estimation capabilities, we created a solution that provides real-time feedback on posture and automatically counts repetitions.
The model was extensively quantized to run efficiently on TensorRT-enabled mobile devices, making professional-level exercise guidance accessible to everyday users.
Implemented a temporal consistency algorithm to maintain accurate pose estimation even when parts of the body are temporarily occluded.
Optimized inference frequency and developed an adaptive processing pipeline that adjusts computation based on movement intensity.
Created a comprehensive dataset of over 50 common exercises and trained a separate lightweight classifier for exercise identification.
"This technology has transformed our personal training app. Users report significant improvement in form and fewer injuries since implementing the pose detection system."
Alex Chen
CTO, FitTech Solutions
