NetFocus
The Project
This research presents an AI-powered basketball shot analysis system that integrates YOLO object detection and pose estimation to evaluate shooting mechanics. The system detects key components such as basketball, hoop, and player movement, while tracking elbow, shoulder, and knee angles to assess shot accuracy and provide actionable feedback. By providing automated, AI-driven shooting feedback, this system offers a cost-effective alternative to personal coaching, making basketball training more accessible, efficient, and data-driven for players at all skill levels. The challenge is to provide a cost-effective and accessible solution that enables players to receive real-time feedback on their shooting form without needing a personal coach. Ensuring accurate motion tracking was another major challenge. The app relies on a smartphone camera to track key points on a player's body, including shoulders, elbows, wrists, knees, and ankles, to analyze shooting mechanics. A key challenge in developing the basketball shot analysis system was ensuring accurate object detection and shot assessment using YOLO (You Only Look Once). One of the primary challenges in developing the basketball shot analysis app is designing an intuitive and efficient user interface.
