The dataset provides structured ground-truth labels for each image, which are often used as the "features" to be predicted or as conditional inputs: True chronological age (ranging from 16 to 77 years). Binary classification (Male/Female). Race/Ethnicity:
Here is a detailed breakdown of the dataset, its composition, and its significance in the research community.
Roughly 4 images per individual, allowing algorithms to track progressive chronological changes. Age Range: Covers individuals from 16 to 77 years old. Demographic Breakdown morph ii dataset
| Feature | Details | | :--- | :--- | | | Longitudinal MORPH Album 2 | | Release Year | 2008 (non-commercial) | | Total Images | ~55,134 | | Unique Subjects | ~13,617 | | Age Range | 16 to 77 years | | Average Age | ~33 years | | Primary Ethnicities | ~77% African-American, ~19% Caucasian, ~4% Other | | Key Metadata | Age, Gender, Race, DOB, Capture Date | | Main Applications | Age Estimation, Face Recognition, Demographic Analysis | | Key Weaknesses | Demographic bias, metadata inconsistencies, pre-processing required |
These offer precise GitHub splits to ensure consistent comparison across different studies. 3. Notable Subsets and Features The dataset provides structured ground-truth labels for each
The longitudinal aspect is critical; it provides multiple images of the same individuals over time, allowing for the study of how a face changes, rather than just what a face looks like at a single point in time. Key Characteristics and Demographics
Despite its popularity, the MORPH II dataset has limitations: Roughly 4 images per individual, allowing algorithms to
Developing facial recognition systems that can accurately identify a person even if the query photo is taken years apart from the gallery photo.