Consent
Define the intended use, capture only what is necessary, and explain how the data will be handled.
Computer vision · Fitment · Human geometry
Fit should be measured.
MaskFitter is exploring privacy-conscious ways to translate human geometry into more informed equipment-fit decisions.
- MapCapture relevant geometry
- MeasureConvert shape into usable data
- MatchCompare the person and equipment
The problem
Generic sizing leaves fit to trial and error.
Equipment that interfaces with the face is often selected through broad size categories, subjective judgment, or repeated physical trials. MaskFitter’s thesis is that computer vision and geometric comparison can make that process more consistent and informative.
The concept is not limited to a single mask category. The underlying question is broader: how can a person’s relevant geometry be compared with equipment geometry before a fit decision is made?
Proposed workflow
Geometry before recommendation.
Capture
Create a fitment-oriented geometric profile from a compatible device or imaging workflow.
Compare
Evaluate the profile against structured equipment dimensions and fit requirements.
Validate
Test recommendations against verified outcomes before making performance claims.
Privacy and evidence
Fitment data should not become identity surveillance.
The intended system is geometry-led, not identity-led. A future product would require explicit consent, data minimization, retention controls, security, and clear limits on secondary use.
MaskFitter is an exploratory concept. It is not currently a medical device, occupational-safety certification, or guarantee of protection. Any medical, tactical, or protective-performance use would require appropriate technical validation and regulatory review.