Video · Image / Education
Abandoned Object Detection Video Dataset - 1,062 Videos for Public Safety and Computer Vision
Advertised by providerLicensing rights not independently verifiedPaid licence
Overview
Abandoned Object Detection Video Dataset - 1,062 Videos for Public Safety and Computer Vision is a video and image dataset. The provider states a volume of 1,062 videos. Typical applications include alignment & RLHF and object detection. Relevant sectors: Education, AI & Machine Learning and Public Sector & Legal. It is offered as a paid dataset; pricing details are provided on request.
Primary applications
What the listing offers
- Stated volume of 1,062 videos.
Overview The Abandoned Object Detection Video Dataset (referred to on the site as the ABODA dataset) is a commercial video dataset produced by the provider. It includes 1,062 Full HD videos of simulated abandoned object scenarios: in each one, a person leaves an object in the frame and walks away. The videos were captured outdoors from a static camera at 1920×1080 resolution and 30 FPS across approximately 60–70 locations, and they feature 50 object types. Dataset at a Glance 1. Total number of files: 1,062 videos 2. Data type: video 3. Video format: MP4 3. Resolution: 1920×1080 (Full HD) 4. Frame rate: 30 FPS 5. Camera perspective: static 6. Environment: outdoors 7. Number of locations: ~60–70, with no more than 3 videos per location 8. Number of object types: 50 9. Clothing change: every 10 videos 10. Tasks: public safety, computer vision Scenario Structure Each video follows a consistent simulated scenario: - A person enters the scene with an object. - The person leaves the object in the frame. - The person walks away, and the object remains in place. This structure lets detection methods learn the moment when an object becomes separated from nearby people. It supports systems that detect abandoned objects and identify when a bag was left behind in video surveillance. Time of Day Distribution The dataset is almost evenly balanced between daytime and low-light recordings: - Day: 549 videos (51.69%) - Evening/night: 513 videos (48.31%) Lighting Distribution Lighting conditions fo
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- Language
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