Cabin Driver Behavior and State Perception for Safe Driving Monitoring Dataset
- Records
- 22584
- Size
- 1.2GB
- Format
- piece
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
This dataset contains in-cabin images for perceiving driver behavior and state, along with image identifiers, image paths, annotation file paths, class IDs, image dimensions, and image formats. It supports research and development in driver-state recognition and safe-driving monitoring, including the training and evaluation of in-cabin vision models. Typical applications include detecting driver distraction or abnormal states, developing driver monitoring systems, and validating intelligent-cabin safety features.
Overview
Dataset Insights
Preview
Sample Examples
59d6fcdc**.jpg||0 B
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| image_id | string | A unique identifier for the image record. |
| image_path | string | The file path or location of the image. |
| label_path | string | The file path or location of the annotation associated with the image. |
| category_id | array | The identifier for the image's assigned class. |
| image_width | number | The width of the image in pixels. |
| image_format | string | The image file format. |
| image_height | number | The height of the image in pixels. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
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
FAQ
Frequently Asked Questions
- What does the dataset contain?
- It contains in-cabin images related to drivers, together with fields for image identifiers, image and annotation file paths, class IDs, image dimensions, and image formats. These fields help link images with annotations and basic image specifications.
- Are the total sample count and image resolution specified?
- The available information does not specify the total number of samples or a defined resolution range. Width, height, and image format fields are provided so these specifications can be checked for individual images after access.
- How can I access and use the dataset?
- Obtain the images and corresponding annotation files through the dataset listing or from the data provider. Use the image paths, annotation file paths, and class IDs to load and organize the data. Available file formats and delivery methods depend on the provider's release details.
- What are the dataset licensing terms?
- Specific licensing terms are not included in the available information. Before use, consult the dataset listing or contact the provider to confirm permitted use, commercial-use rights, and applicable privacy and compliance requirements.
- Which model development tasks does it support?
- The data can support training and evaluation for driver-state classification, behavior recognition, and related in-cabin vision tasks. It may also assist in developing fatigue or distraction monitoring, safe-driving alerts, and intelligent-cabin monitoring features. Results depend on the class definitions, annotation quality, and data coverage.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
High-quality data, ready for your next AI breakthrough.
Cite this Work
@dataset{Mobiusi2026,
title={Cabin Driver Behavior and State Perception for Safe Driving Monitoring Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/2241d1dde9805f00b1c6ac5776596bd6?dataset_scene_cate_type=6},
urldate={2026-11-05},
keywords={driver behavior dataset,in-cabin monitoring data,driver state recognition,fatigue driving detection,distracted driving recognition,safe driving monitoring,intelligent cabin vision,driving behavior recognition},
version={1.0}
}Using this in research? Please cite us.