# Nose Tip Position

Harmony · Front view · Nose · https://www.faceiqlabs.com/support/harmony/nose-tip-position

The vertical offset of the nose-bottom landmark from the nasal-base landmark in the front photo.

## What is measured

Calculation: (Nose-bottom y − nasal-base y) × photo scale

## Why it matters

This describes the front-view relationship between the tip region and the nose base. It can help explain the visible nose-to-upper-lip transition without confusing it with sideways deviation.

- Negative: the nose-bottom landmark is above the nasal base.
- Positive: the nose-bottom landmark is below the nasal base.

## Where the idea comes from

Evidence: FaceIQ adaptation. This is a FaceIQ landmark-based description of facial shape. The linked research provides background on facial measurement or perception; it has not directly validated this exact formula or its score.

## A worked example

With a photo scale of 0.2 estimated mm per unit, a nose-bottom landmark 10 units below the nasal base gives +2 mm.

Example values explain the calculation. They are not a target range.

## How to read your result

This is a vertical measurement, not a test of whether the tip is centered left-to-right. Looking up or down changes it.

Millimeters are approximate: FaceIQ scales the photo using an assumed 190 mm hairline-to-chin height, so these are estimates, not calibrated physical measurements.

## Research & further reading

These sources explain the history or related evidence. FaceIQ’s score weights and reference ranges are model settings; the papers do not collectively validate the scoring system.

- Tavakoli et al. (2023). [Ideal Nasal Preferences: A Quantitative Investigation with 3D Imaging in the Iranian Population](https://pubmed.ncbi.nlm.nih.gov/37564715/). Asked 203 volunteers to rate edited nose features on one male and one female model. Supports studying angles and projection together, with limits from the sampled faces and raters.

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Source: https://www.faceiqlabs.com/support/harmony/nose-tip-position · FaceIQ Labs overview for AI assistants: https://www.faceiqlabs.com/llms.txt