3D Face Recognition Images Sample with Multiple Postures and Lighting

Sample of 5,199 3D face images from 5,199 people, collected in an indoor scene. It includes males and females with an age distribution from juvenile to elderly, primarily young and middle-aged people, captured using iPhone X and iPhone XR devices.

Use Cases

• Train a 3D face recognition model on images with multiple facial postures to improve pose invariance.
• Analyze the impact of multiple lighting conditions on 3D facial feature extraction algorithms.
• Develop demographic analysis models using the age distribution and gender data associated with the images.

Strengths

• Contains 5,199 images from 5,199 distinct individuals, providing a sample of unique identities.
• Includes multiple facial postures and multiple lighting conditions, introducing data diversity.
• Covers an age distribution from juvenile to elderly, with young and middle-aged people as the majority.

Limitations

• The dataset is explicitly a sample of a larger paid dataset, limiting its scale and completeness.
• Collection is limited to an indoor scene and specific devices (iPhone X, iPhone XR), which may reduce environmental and hardware diversity.
• Demographic details like exact age, gender labels, or posture/lighting annotations are not specified in the available metadata.

Provenance

Source

Nexdata

Collection Method

Collected in an indoor scene using iPhone X and iPhone XR devices.

Freshness

Last updated on 2025-04-24.

Geography

Region tag indicates 'us', but specific geography is not detailed in the summary.