Impared Computer Vision Project

MachineNov

Updated 10 months ago

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Classes (6)
child
crutches
person
push_wheelchair
walking_frame
wheelchair

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Description

Here are a few use cases for this project:

  1. Accessibility Assessment: The "Impared" model could be used to analyze CCTV or other public area footage to help city planners or administrators measure the usage of public spaces and facilities by differently-abled groups. This could inform necessary improvements or additional facilities for these individuals.

  2. Automated Personal Assistance: Developers could use this model to design assistive AI-powered robots or devices which can recognize and understand the specific mobility needs of differently-abled people, providing help when necessary, like opening doors or alerting human helpers.

  3. Healthcare Monitoring: The model can be utilized for monitoring patients in a nursing home or hospital setup, tracking the movement of patients with different physical impairments, providing feedback to medical staff or aid in emergency situations.

  4. Smart Home Automation: This model could be integrated into smart home systems to customize responses based on the recognized individual, enhancing personalized user experiences for people with mobility impairments.

  5. Security Systems: Improve the inclusivity and efficiency of security systems by using the Impared model to recognize individuals with mobility aids, ensuring the systems adapt appropriately.

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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{
                            impared_dataset,
                            title = { Impared Dataset },
                            type = { Open Source Dataset },
                            author = { MachineNov },
                            howpublished = { \url{ https://universe.roboflow.com/machinenov/impared } },
                            url = { https://universe.roboflow.com/machinenov/impared },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { feb },
                            note = { visited on 2024-11-24 },
                            }
                        
                    

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