주목할 발표 · Indy Ho
세션 소개
Python is currently widely used in solving research and application problems in the sports science, injury prevention, and physical fitness promotion areas. This talk will be divided into two sections. The first part will go through the existing literature regarding the current popular use of Python in solving different sports-related problems. Meanwhile, the first speaker will also show predictive analytics using machine/deep learning with Python scripts in biomechanical applications using IMU sensors and force plate data to help solve sports injury prevention problems. The second part will focus on the use of Python for motion capture and human movement analysis.
To collect human biomechanics data for sports and motion analysis, camera-based pose estimation with AI has become a popular alternative to Inertial Measurement Units (IMUs). While MediaPipe's pose tracking library may be the first one that comes up when you Vibe Code an application that needs human poses. But MediaPipe is just one option among many. Pose estimation libraries span from open-source to commercial, 2D and 3D output, prioritize either real-time inference speed or high-fidelity accuracy, and deployment complexity. In this section, we will explore the different approaches to pose estimation, how to choose the right one for your use case, and live demos of pose estimation in Python.
This part will include "The Landscape", as an exploration of different approaches to pose estimation, ranging from lightweight 2D skeletal tracking to more complex 3D kinematic modeling; "Choosing Your Stack" as a practical guide to evaluating trade-off; "hardware constraints, speed vs. accuracy, and ease of deployment" for showing the right library for your specific use case and; "Live Demos" for switching from slides to code, demonstrating pose tracking with YOLO-Pose. Here, participants can see how to track fast, complex physical mechanics with just a few lines of code.
This will be a great opportunity for us to exchange ideas and open the door to prepare for the future of sports, exercise, and human performance enhancement.
발표자 소개
Indy Ho
Indy Ho is a registered physiotherapist and an Assistant Professor at the Technological and Higher Education Institute of Hong Kong. His research interests include sports science, sports therapy, strength and conditioning, data science, and machine learning. After obtaining his second master's degree in Data Science, he currently is studying in PhD to apply machine or deep learning for predictive analytics using IMU sensor data to realise the landing force and stability.