Mobiusi

Bank Counter Visitor Reception Image Dataset

#image recognition #object detection #behavior analysis #visitor management #identity verification #security surveillance
  • 500 records
  • 1.3G
  • JPG
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-02-04

AI Analysis & Value Prop

Current bank counter visitor management faces challenges in automation and accuracy. Traditional methods rely on manual recognition, which is inefficient and prone to errors, especially during high traffic periods. Existing automatic recognition systems still have issues with low recognition rates and poor interference resistance. This dataset aims at identification and behavior analysis of bank counter visitors, addressing automation and precision in the reception process. Data is collected through high-definition cameras in a simulated bank counter environment, capturing visitor reception scenarios under different lighting and crowd conditions. To ensure data quality, a triple annotation process with multiple rounds of consistency checks is employed, ensuring annotation accuracy exceeds 95%. The annotation team consists of 5 image processing experts. The data undergoes preprocessing such as noise removal and lighting balance, and is saved in a structured JPG format, organized by date and camera number.

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
visitor_countintThe number of visitors appearing in the image.
employee_countintThe number of bank employees appearing in the image.
interaction_typestringThe type of interaction between the visitor and bank employee in the image, such as inquiry or transaction.
queue_lengthintThe number of visitors waiting in line in the image.
visitor_emotionstringThe emotional state of the visitors in the image, such as happy or frustrated.
visitor_age_groupstringThe approximate age group of the visitors in the image, such as young, middle-aged, or elderly.
visitor_genderstringThe gender of the visitor in the image.
transaction_typestringThe type of transaction being conducted in the image, such as deposit or withdrawal.
time_of_daystringThe time of day when the image was taken, such as morning or afternoon.

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What application scenarios are suitable for the bank counter visitor reception image dataset?
This dataset is suitable for improving bank counter visitor management, automated recognition, and security systems.
How to use the bank counter visitor reception image dataset for machine learning model training?
You can use this dataset to train computer vision models to recognize and classify bank counter visitors, thereby improving management efficiency.
What are the technical advantages of the bank counter visitor reception image dataset?
The dataset provides high-quality image data, useful for developing advanced recognition algorithms and improving the accuracy of automated visitor management systems.
How to assess the diversity of the bank counter visitor reception image dataset?
The dataset may include images with various angles, lighting, and crowd characteristics to enhance the model's robustness.
Who are the potential user groups of the bank counter visitor reception image dataset?
Potential users include bank security system developers, automated visitor management software companies, and computer vision researchers.

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Cite this Work

@dataset{Mobiusi2026,
  title={Bank Counter Visitor Reception Image Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/fdba4874f2ff665805cf6576d1089a87},
  urldate={2026-02-04},
  keywords={bank counter image dataset, visitor management dataset, bank security surveillance dataset},
  version={1.0}
}

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