Corridor and Public Passage Occupation Image Recognition Dataset
#Image Classification #Object Detection #Scene Understanding #Intelligent Monitoring #Building Management #Safety Inspection
- 500 records
- 1.5G
- JPG
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
Currently, many buildings and public spaces face problems with passage occupation, which affects normal passage and safety during emergency evacuations. Existing manual inspections and monitoring systems are prone to missed detections and false detections, and are inefficient. This dataset aims to solve the problem of automated identification of corridor occupation through machine learning and computer vision technologies to improve monitoring efficiency and accuracy. Data collection is conducted using high-resolution camera equipment in real corridor and public passage environments to ensure data diversity and authenticity. Quality control measures include multiple rounds of annotation, consistency checks, and expert reviews. The annotation team consists of 20 professionals with backgrounds in computer vision and image processing. Preprocessing steps include image denoising, light balancing, and target area annotation. The data is organized in a folder structure categorized by scenes, stored in JPG format.
Dataset Insights
Sample Examples
6459223a**.jpg|1080*1392|154.25 KB
3fa0a3f4**.jpg|1080*1397|372.53 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| scene_type | string | The type of scene, such as a corridor or public passageway. |
| occupancy_level | string | The degree to which the passageway is occupied, such as clear, partially occupied, or fully occupied. |
| object_count | int | The number of objects in the passageway. |
| object_type | string | The type of objects identified, such as furniture, equipment, people, etc. |
| light_condition | string | The lighting condition in the image, such as bright or dim. |
| crowd_density | string | The density of the crowd in the corridor or passage, such as low, medium, or high. |
| path_obstruction | string | Whether there is an obstruction in the corridor or passageway. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What scenarios can this dataset be used for?
- This dataset can be used for identifying and detecting occupancy in corridors and public passages, assisting in applications like building management and security monitoring.
- What types of images are included in this dataset?
- The dataset mainly includes images of different occupancy situations in corridors and public passages.
- How to evaluate the quality of this dataset?
- The quality of the dataset can be evaluated by image clarity, diversity of covered scenarios, and the accuracy of annotations.
- Why is it important to recognize the occupancy of corridors and public passages?
- Identifying the occupancy of corridors and public passages is important for enhancing safety, optimizing space usage, and ensuring clear emergency evacuation paths.
- How does this dataset enhance energy-saving and resource management?
- By identifying occupancy scenarios, it can optimize the use of lighting and ventilation systems, thus saving energy and improving resource management efficiency.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Corridor and Public Passage Occupation Image Recognition Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/fefb404e709af4bc86fc40c90e4b5906},
urldate={2026-02-04},
keywords={Corridor Occupation Recognition, Public Passage Detection Dataset, Image Classification Dataset},
version={1.0}
}Using this in research? Please cite us.
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