UMD-Doors Computer Vision Project

UMDDoors

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Description

Here are a few use cases for this project:

  1. Smart Security Systems: The UMD-Doors model could be used to enhance security systems in homes, offices, and public buildings. It could detect when a door or handle is being manipulated and read any associated text that might give information about its use or access control (e.g., "Private", "Staff Only"). This can trigger security measures or alerts.

  2. Assisted Living Technologies: For people with visual impairments or cognitive difficulties, the model can help identify doors and their handlers. This could support navigation and daily living within their homes or care facilities.

  3. Architectural Analysis: Developers, Architects, or Urban planners can use this model to gather data about door design and placement in different environments for their analysis and building designs.

  4. Augmented Reality (AR) Applications: The UMD-Doors model can be used to develop AR apps that overlay digital information on real-world doors, such as details about who resides in a building, operation hours in case of commercial establishments, or history about historical buildings.

  5. Maintenance and Repair Services: Companies can use this model to streamline their services by automatically recognizing door type or handle model, or by reading the text to identify any special maintenance instructions or guidelines.

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Cite This Project

LICENSE
MIT

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

                        @misc{
                            umd-doors_dataset,
                            title = { UMD-Doors Dataset },
                            type = { Open Source Dataset },
                            author = { UMDDoors },
                            howpublished = { \url{ https://universe.roboflow.com/umddoors/umd-doors } },
                            url = { https://universe.roboflow.com/umddoors/umd-doors },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-11-18 },
                            }