Bird Eye View Instance Segmentation Dataset and Pre-Trained Model by Mohamed Badreldin

Images

2116 images

Explore Dataset

Here are a few use cases for this project:

Soccer Game Analysis: The "Bird Eye View" model can be utilized by soccer coaches and analysts to study team formations, player positioning, and strategy development during a soccer match. By identifying specific regions of the field, automated heat maps and spatial statistics can be generated.
Player Performance Evaluation: The model can be employed for evaluating individual player performance during a soccer match by recognizing the players' movement, positioning, and ball control within specific areas of the field, such as the 18-yard box or central circles.
Sports Broadcasting and Media Content: With the ability to identify different sections of a soccer field, the "Bird Eye View" model can enhance telecasts, post-match analysis, and online soccer content with graphics and overlays that display relevant information corresponding to specific areas on the pitch.
Athlete Training and Development: The model can prove valuable for sports academies and athletic trainers by assessing players' spatial awareness, technical skill execution, and decision-making abilities in different sections of the field during practice sessions or simulated games.
Augmented Reality Applications: The "Bird Eye View" model can provide a foundation for developing augmented reality applications, such as apps that help soccer players visualize and understand tactical movements, positioning, and strategies in real-time using their mobile devices or wearables on the field.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            bird-eye-view_dataset,
                            title = { Bird Eye View Dataset },
                            type = { Open Source Dataset },
                            author = { Mohamed Badreldin },
                            howpublished = { \url{ https://universe.roboflow.com/mohamed-badreldin-cp2tc/bird-eye-view } },
                            url = { https://universe.roboflow.com/mohamed-badreldin-cp2tc/bird-eye-view },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-06-18 },
                            }