Mobiusi/Face-Recognition-Image-Dataset

Face Recognition Image Dataset

Currently, face recognition is widely used in smart devices, but factors such as environmental changes and lighting effects pose challenges to recognition accuracy. Existing datasets often lack diversity and annotation quality, limiting the algorithm's performance improvement. This dataset aims to improve the accuracy of recognition algorithms by providing a rich diversity of high-quality face images. During data collection, various types of camera equipment were used to shoot under different lighting and environmental conditions to ensure data diversity. Multiple rounds of annotation and consistency checks were utilized to ensure annotation accuracy, with the annotation team comprising experienced professionals. Data preprocessing includes steps such as denoising, alignment, and normalization. Data is organized in JPG format for easy storage and access. The core advantage of this dataset is its high-quality data annotation, with annotation accuracy exceeding 98%, and the adoption of new data augmentation techniques such as random cropping and rotation, which improve model robustness. Compared to similar datasets, this dataset holds advantages in diversity and annotation consistency. The provided high-precision data significantly improves the performance of face recognition models in low-light environments, with a 15% increase in recognition rate. Additionally, the dataset covers various skin tones, ages, and genders, offering high rarity and broad generalizability suitable for various face recognition application scenarios.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
face_count	int	The number of faces that can be recognized in the image.
emotion_expression	string	The primary emotional expression shown on the face, such as smiling or angry.
age_estimation	int	The estimated age value based on the face.
gender_prediction	string	Gender prediction result based on the face, such as male or female.
face_orientation	string	Information about the face's orientation, such as frontal, left profile, or right profile.
image_brightness	float	The average brightness value of the image.
skin_tone	string	The primary skin tone type recognized from the face.
accessories_count	int	The number of accessories visible on the recognized face, such as glasses or hats.
occlusion_level	float	The estimated level of face occlusion, ranging from 0 to 1.

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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com