Development of Facial Authentication Framework
Purpose: Testing out different frameworks and their performance.
Outcomes
You should have at least one facial authentication model that matches your benchmark and criteria for implementation in the main project.
Steps To Complete
- Find out different models and implement them.
- Consider parameters needed to get the best performance, (e.g. images needed for training, frame rate, confidence rating, etc.)
- Note the final parameters with dependencies needed to be followed by documentation for the process.
Acceptance Criteria
It will be considered valid if the model consistently gives a confidence rating of at least 80-85%.