AI-Based Football Video Analytics – Research Project
Budget / Salary₹2,200–2,500
TypeFreelance project
LocationRemote
Posted1 hour ago
AI-Based Football Video Analytics – Research Project
I’m looking for an AI/ML + Computer Vision developer/researcher to develop an experimental research prototype + research paper on:
“AI-Based Low-Cost Video Analytics System for Assisting Grassroots Football Talent Identification.”
Project Scope
I already have football video footage. The goal is to build a research-level prototype, not a commercial application.
Workflow:
Football Video → Preprocessing → Player Detection (YOLO) → Player Tracking (ByteTrack/BoT-SORT) → Movement/Position Analysis → Feature Extraction → Player Performance Metrics → Analytical Player Profile
Possible metrics include distance, estimated speed, movement intensity, trajectories, field/zone coverage, and other reliably measurable indicators.
Experimental Requirements
The implementation must produce genuine quantitative results, including where applicable:
-Detection: Precision, Recall, F1, mAP
-Tracking: IDF1, ID switches/MOTA
-Performance: FPS, processing time
-Player-wise performance analysis
-Graphs, tables and visualized/annotated video results
-Model/approach comparison where feasible
No fabricated results.
Research Paper Format
Abstract → Keywords → Introduction → Literature Review & Research Gap → Methodology → Dataset & Experimental Setup → Experiments & Results → Comparative Analysis → Discussion → Limitations → Conclusion → Future Work → References
The paper should include system architecture/workflow, literature comparison table, methodology diagrams, experimental tables/graphs, and relevant visual results.
Technology
Python, OpenCV, YOLO/PyTorch, ByteTrack/BoT-SORT or suitable alternatives. Pretrained models are acceptable; no need to build a model from scratch.
Deliverables
-Working prototype + source code
-Experimental results
-Tables/graphs/visualizations
-Architecture/workflow diagram
-Complete research paper
-Proper academic references
Publication Goal:
Target a legitimate peer-reviewed Scopus-indexed venue, preferably a suitable IEEE/Springer or other relevant journal/conference, subject to the final quality and current indexing status.
Important: This is a research prototype + experimental paper, not a full commercial software system. I already have the football footage.
Please apply only if you have experience in Computer Vision/YOLO, tracking, Python, sports analytics and academic research.
I’m looking for an AI/ML + Computer Vision developer/researcher to develop an experimental research prototype + research paper on:
“AI-Based Low-Cost Video Analytics System for Assisting Grassroots Football Talent Identification.”
Project Scope
I already have football video footage. The goal is to build a research-level prototype, not a commercial application.
Workflow:
Football Video → Preprocessing → Player Detection (YOLO) → Player Tracking (ByteTrack/BoT-SORT) → Movement/Position Analysis → Feature Extraction → Player Performance Metrics → Analytical Player Profile
Possible metrics include distance, estimated speed, movement intensity, trajectories, field/zone coverage, and other reliably measurable indicators.
Experimental Requirements
The implementation must produce genuine quantitative results, including where applicable:
-Detection: Precision, Recall, F1, mAP
-Tracking: IDF1, ID switches/MOTA
-Performance: FPS, processing time
-Player-wise performance analysis
-Graphs, tables and visualized/annotated video results
-Model/approach comparison where feasible
No fabricated results.
Research Paper Format
Abstract → Keywords → Introduction → Literature Review & Research Gap → Methodology → Dataset & Experimental Setup → Experiments & Results → Comparative Analysis → Discussion → Limitations → Conclusion → Future Work → References
The paper should include system architecture/workflow, literature comparison table, methodology diagrams, experimental tables/graphs, and relevant visual results.
Technology
Python, OpenCV, YOLO/PyTorch, ByteTrack/BoT-SORT or suitable alternatives. Pretrained models are acceptable; no need to build a model from scratch.
Deliverables
-Working prototype + source code
-Experimental results
-Tables/graphs/visualizations
-Architecture/workflow diagram
-Complete research paper
-Proper academic references
Publication Goal:
Target a legitimate peer-reviewed Scopus-indexed venue, preferably a suitable IEEE/Springer or other relevant journal/conference, subject to the final quality and current indexing status.
Important: This is a research prototype + experimental paper, not a full commercial software system. I already have the football footage.
Please apply only if you have experience in Computer Vision/YOLO, tracking, Python, sports analytics and academic research.
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