How does AI face comparison work?
AI face comparison does not “recognize family” the way a person does. It analyzes visible patterns in face images and estimates how similar those patterns are.
1. The face is detected in each photo
Before two images can be compared, the system first needs to locate the face. A clear, unobstructed face usually gives the model a better starting point than a small, blurred or partially hidden face.
2. Facial information is converted into numbers
Modern face-analysis systems represent a face using a numerical embedding: a compact set of values that describes visual characteristics learned by the model. The embedding is not a written description of the person. It is a mathematical representation that allows two faces to be compared consistently.
3. The numerical representations are compared
The system measures how close or far apart the two representations are. Faces with more similar visual patterns generally produce a stronger similarity score, while larger differences produce a lower score.
4. Why the same people can receive different scores
A face is three-dimensional, while a photo is only one view of it. Camera angle, distance, expression, lighting, age, makeup, facial hair, image compression and even the quality of the camera can change what the model sees.
What LooksCompare uses the score for
LooksCompare is designed as a family and entertainment tool. In the family test, the child photo is compared separately with the mom and dad photos. The resulting percentages help show which comparison appears visually closer under the uploaded conditions.
How to improve consistency
- Use frontal or near-frontal photos.
- Choose images with good, even lighting.
- Avoid strong beauty filters.
- Keep the full face visible.
- Use photos taken at reasonably similar ages when possible.