Golf is a sport where technique and precision are crucial. Analyzing a golf swing can help players improve their performance significantly. In this blog post, I'll share how I used the RTMO (Real-Time Multi-person Object) Pose Estimation technique to analyze golf swings from video footage. Pose-Estimation using RTMO RTMO is a cutting-edge technique for real-time multi-person pose estimation. Unlike traditional methods, RTMO integrates coordinate classification within the YOLO architecture, enabling high accuracy and real-time performance. This technique uses dual 1-D heatmaps to represent keypoints, achieving accuracy comparable to top-down methods while maintaining high speed.
The objective of this project was to capture and analyze a golf swing from video footage. Using RTMO Pose Estimation, I aimed to estimate key points on the golfer's body and visualize these key points along with bounding boxes and skeletons on the video frames.
How It Works
Input Video: The process begins by capturing video footage of a golf swing.
Pose Estimation: Each frame of the video is processed using the RTMO model to estimate the key points of the golfer's body.
Visualization: The estimated key points, bounding boxes, and skeletons are drawn on the video frames, allowing for a visual analysis of the golfer's posture and movements.
Results
The output video shows the golfer's swing with overlaid key points, bounding boxes, and skeletons. This visual representation is highly beneficial for analyzing the biomechanics of the swing, helping to identify areas for improvement.
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