Ped dataset with novel classes Computer Vision Project

University of Washington

Updated 2 years ago

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Description

Here are a few use cases for this project:

  1. Urban Planning & Infrastructure Development: This model can be used by local governments or city planners to analyze pedestrian, cyclist, and wheelchair user traffic in certain areas. It would be valuable in determining the need for infrastructure improvements such as building more bike lanes, pedestrians crossings, or wheelchair-accessible facilities.

  2. Assistive Technology: The model can help create advanced assistive technologies for wheelchair users. For instance, an automated navigation system detecting other pedestrians, bicycles, or wheelchair users and suggesting an optimal path.

  3. Surveillance System Enhancement: The model can be used to enhance security and surveillance systems, being able to differentiate between pedestrians, cyclists, and wheelchair users. This information can be crucial when reviewing any footage for criminal activity, accidents, or safety checks.

  4. Traffic Management: Traffic management systems can leverage this model to dynamically manage traffic lights based on the volume and type of road users detected.

  5. Retail Planning: Retail businesses could use this model to analyze the types of customers passing by or entering their store, allowing them to adapt their services and product offerings to better serve the needs of pedestrians, cyclists, or wheelchair users.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            ped-dataset-with-novel-classes_dataset,
                            title = { Ped dataset with novel classes Dataset },
                            type = { Open Source Dataset },
                            author = { University of Washington },
                            howpublished = { \url{ https://universe.roboflow.com/university-of-washington-xdvzb/ped-dataset-with-novel-classes } },
                            url = { https://universe.roboflow.com/university-of-washington-xdvzb/ped-dataset-with-novel-classes },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-12-27 },
                            }
                        
                    

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