Semantic Segmentation

real_ces Computer Vision Project


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Explore Dataset

Here are a few use cases for this project:

  1. Smart Security System: Using the "real_ces" model, security cameras can detect the presence of people in restricted areas, ignoring chairs as false-positives, and alert security personnel of potential unauthorized access.

  2. Home Automation and Energy Management: Integrate the model in smart home devices to track whether a person is sitting on a chair or if a room is unoccupied. With this information, the devices can automatically adjust lighting, temperature, or entertainment systems based on occupancy.

  3. Retail Store Analysis: Implement the "real_ces" model to analyze customer behavior in retail stores, such as time spent sitting on chairs, foot traffic patterns, and determining the effectiveness of different store layouts.

  4. Accessibility Assistance: The model can be used in applications for visually impaired individuals, helping them navigate public spaces by detecting and describing nearby chairs or people, hence allowing them to find a seat or avoid a person in their path.

  5. Workplace Monitoring and Safety: Integrate the model into workplace monitoring systems to ensure adherence to health and safety guidelines by tracking the presence of people and designating proper seating arrangements for employees, clients, or other visitors.

Cite this Project

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

@misc{ real_ces_dataset,
    title = { real_ces Dataset },
    type = { Open Source Dataset },
    author = { meere },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { sep },
    note = { visited on 2023-12-02 },

Find utilities and guides to help you start using the real_ces project in your project.



Last Updated

3 months ago

Project Type

Semantic Segmentation




chair, person

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CC BY 4.0

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