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羽毛球比赛视频智能分析 | Badminton match video analytics: TrackNet shuttle detection + YOLOv8s-pose player tracking + court homography + bullet-time FX. Runs end-to-end on Apple Silicon. 完整文档与 AI agent 任务包见 HANDOVER.md
Robust Player Tracking & Behavior Analysis pipeline for SoccerNet Benchmark. Features YOLO11x, BoT-SORT (GMC), and Adaptive Field Masking. Artificial Vision Project 2025/26 @ Unisa.
Soccerlytics is an comprehensive football video analysis system that tracks and analyzes matches. It generates enhanced visualizations with player tracking, ball possession statistics, team assignments, and a unique 2D top-down view for tactical analysis.
Football player detection, tracking, and re-identification from video using YOLOv11, IoU-based motion matching, and appearance-based ReID with HSV feature descriptors.
Football match video analysis using computer vision. Features YOLO object detection, ByteTrack player tracking, unsupervised team classification, and 2D pitch minimap generation.
Deep learning pipeline for player detection and analytics using YOLO, DeepSORT, and custom metrics covers model training, tracking, feature extraction, insights, and visualization for sports data.
Automated football match event detection from broadcast video — YOLOv8 player/ball detection, real-time tracking, interactive player tagging, replay filtering, and structured event output for sports analytics workflows.
Real-time soccer player tracking & re-identification with YOLOv11, plus a benchmarked comparison of ByteTrack, BoT-SORT, DeepSORT, and Norfair on 720p/4K footage. Python · OpenCV · Ultralytics.
Local-first macOS hockey video analysis pipeline (Computer Vision) that stitches LiveBarn game segments, aligns HockeyTracker/Apple Watch shifts, tracks a selected player, maps rink zones, detects events, and exports detailed match analytics to CSV.