# FaceAttribute - Android

## Overview

This demo project integrates several facial recognition technologies, including 3D passive face liveness detection, face recognition, automatic face capture, and analysis of various face attributes such as age, gender, face quality, facial occlusion, eye closure, and mouth opening.

The system utilizes face liveness detection technology to generate a real-time liveness score based on a single image captured by the camera.

Additionally, the demo offers face recognition capabilities, enabling enrollment from a gallery and real-time identification of faces captured by the camera.

The demo also features an automatic face capture function that verifies various facial attributes, such as face quality, facial orientation (yaw, roll, pitch), facial occlusion (e.g., mask, sunglass, hand over face), eye closure, mouth opening, and the position of the face within the region of interest (ROI).

Moreover, the demo can compute scores for different face attributes from a gallery image, including liveness, face orientation (yaw, roll, pitch), face quality, the luminance of the face, facial occlusion, eye closure, mouth opening, age, and gender.

## SDK

{% content-ref url="../../product/face-liveness-detection-sdk-face-recognition-sdk/premium-sdk-mobile/premium-sdk-android" %}
[premium-sdk-android](https://docs.kby-ai.com/help/product/face-liveness-detection-sdk-face-recognition-sdk/premium-sdk-mobile/premium-sdk-android)
{% endcontent-ref %}

## Github

{% embed url="<https://github.com/kby-ai/FaceAttribute-Android>" %}

## Google Play

{% embed url="<https://play.google.com/store/apps/details?id=com.kbyai.faceattribute&pli=1>" %}

## YouTube

{% embed url="<https://www.youtube.com/watch?v=-WiAethTacc>" %}

## Screenshots

<div><figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FFcrk2Pbt7WMCw5egwHsD%2F235572284-dd230e36-ec37-42aa-9482-35c78a8a7ce7.png?alt=media&#x26;token=e542ecb4-4c7d-437a-967c-d532031fdc02" alt=""><figcaption></figcaption></figure> <figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FyVb1VpGGpL42Cew8hcRG%2F235572299-23989a6e-d6cc-41d3-b75c-a235018ee464.png?alt=media&#x26;token=f7f23aa2-7d0f-4ce3-8910-8f5cd5450b7d" alt=""><figcaption></figcaption></figure> <figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FAOICDLoybOr36jP46dJK%2F235572304-41714fd2-b117-4bcf-999d-32c6d5c1a0c5.png?alt=media&#x26;token=78b426d9-9e86-40ec-a710-94df8025d8dd" alt=""><figcaption></figcaption></figure></div>

<div><figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FnoauVqBR7gMk3pE7ZQeK%2F235572987-c8cdfa0a-34cc-4f29-8b1a-f58288c71eb0.png?alt=media&#x26;token=1fc47e47-cca8-4b99-8ec9-3319c1847780" alt="" width="188"><figcaption></figcaption></figure> <figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FObXOdSoqxx4r0rcRGQZU%2F235573098-8a15bf1a-3930-4b47-b79b-ffb63e9940f2.png?alt=media&#x26;token=1088fbe0-c9b1-4015-9594-167468068b7a" alt="" width="188"><figcaption></figcaption></figure></div>

<div><figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FWd01pJk4p9tgBhiAhcOl%2F235573974-413e09cd-d822-46bb-b0dc-cb0e95a5babc.png?alt=media&#x26;token=3364ec44-708d-4dea-a229-3d5416192c46" alt="" width="188"><figcaption></figcaption></figure> <figure><img src="https://2589216230-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F1WwtQK0VFwKRGmIjGA3I%2Fuploads%2FTtsLmbLrTTh1duHnCw6o%2F235573436-6944cd3b-3b93-404d-b8c7-c02fc83d4bdc.png?alt=media&#x26;token=5629c6e4-5cf4-4607-9e8b-d2146fb506fb" alt="" width="188"><figcaption></figcaption></figure></div>


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