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CCTV Annotations

Urban Big Data Centre (UBDC), and Livingston, M. (2025) CCTV Annotations. [Data Collection]

Collection description

Overview:

The Urban Big Data Centre (UBDC) owns a dataset of 10,446 CCTV-like urban images and respective annotations. In object detection, annotations are structured metadata added to images that specify the locations and categories of objects within the image. These annotations are typically created manually or semi-automatically and are essential for training and evaluating object detection models.

The annotations are made on the objects of interest. Different colours correspond to different object types. These manually annotated images can then be used to train an object detection model. Once trained, the model can, for example, generate its own annotations, which can be recorded in a spreadsheet.

The aim of this dataset is to support computer vision research by providing high-quality, annotated images that enable the development, training, and benchmarking of object detection models. It facilitates experimentation with algorithms, improves model generalization, and contributes to advancements in automated visual recognition systems, particularly in urban scenarios. This is a controlled dataset containing personally identifiable information.

Access and restrictions:

CCTV annotated data is secure, controlled data and the data is not available for research sharing. However, this metadata record has been provided for research data integrity purposes.

More information:

This dataset was created from the source data CCTV Traffic video data. The Urban Big Data Centre runs the Glasgow CCTV Object Detection project in partnership with the Glasgow City Council. Glasgow City Council is responsible for the capture of half-hourly images by all the cameras in the project whereas the Data Science Team at the Urban Big Data Centre is responsible for processing the objects of interest localized on the images and for making this data available to users through their CCTV API. This project aims to develop methods to use CCTV images to produce regular statistics on activity levels in urban areas.

Funding: