Local Binary Patterns for facial recognition
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- University of Oulu,IEEE
- Organisation type
- Academia,Industry
- Country
- Finland, Multinational
- Published
- 1 December 2006
- Authors
- Timo Ahonen, Abdenour Hadid, and Matti Pietikainen
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Image classification
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 736 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Record confidence
- Unknown
- Citations
- 5,915
Sources
Where this record came from and when it was last checked.
- Reference
- Face Description with Local Binary Patterns: Application to Face Recognition
- Last updated
- 1 January 2026
What the numbers mean
Where it came from
Local Binary Patterns for facial recognition was published by University of Oulu,IEEE, in Finland, in December 2006. It comes out of academia,Industry.
It works in Vision, and is recorded as doing image classification.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
It was trained on about 736 tokens of text.
It is tracked in the underlying dataset for one reason in particular: highly cited.
Answers
Local Binary Patterns for facial recognition — common questions
Who created Local Binary Patterns for facial recognition?
Local Binary Patterns for facial recognition was published by University of Oulu,IEEE, based in Finland, categorised as academia,Industry.
When was Local Binary Patterns for facial recognition released?
Local Binary Patterns for facial recognition was published in December 2006. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Local Binary Patterns for facial recognition used for?
Local Binary Patterns for facial recognition works in Vision, and is recorded as handling image classification. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run Local Binary Patterns for facial recognition?
None. Local Binary Patterns for facial recognition is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Local Binary Patterns for facial recognition open source?
The licensing for Local Binary Patterns for facial recognition was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Local Binary Patterns for facial recognition have?
No parameter count has been published for Local Binary Patterns for facial recognition, which is why no memory or speed figure appears on this page.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.