3DWF: 3D Face Point Clouds with RGB-D Images and Subject Demographics
by Quintana González, Marcos / e-cienciaDatos Harvested Dataverse·Updated 2y ago
Available on 1 platform
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Description
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
null
Freshness
Last updated 2024-05-05 07:10:21; freshness should be verified.
Geography
null
License is unknown; terms of use must be verified before download.