3DWF: 3D Face Point Clouds with RGB-D Images and Subject Demographics

A collection of RGB-D camera captures from 92 subjects changing their pose based on 10 markers. The dataset includes images, depth maps, rotation and translation matrices for registration, reconstructed 2K-point clouds, high-definition initial point clouds, and subject characterizations by age, gender, and ethnicity. It was authored by Marcos Quintana González and last updated in May 2024.

Use Cases

• Train 3D face reconstruction models based on the provided RGB-D images and point clouds.
• Develop pose estimation algorithms based on the 10-marker pose change sequence.
• Study demographic correlations in facial structure based on the provided age, gender, and ethnicity labels.
• Benchmark point cloud registration techniques using the provided rotation and translation matrices.

Strengths

• Includes data from 92 distinct subjects, providing a multi-person sample.
• Contains multiple synchronized data types: RGB images, depth maps, and point clouds at 2K and high-definition resolutions.
• Provides subject characterization metadata including age, gender, and ethnicity.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Quintana González, Marcos via e-cienciaDatos Harvested Dataverse

Collection Method

Multi-camera RGB-D capture of subjects following a 10-marker pose sequence.

Time Range

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Freshness

Last updated 2024-05-05 07:10:21; freshness should be verified.

Geography

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