User Face Aging Web Application using Camera

I need a face aging web application for the web browser.

The webapplication should identify the users face in realtime on a video stream (in our case a webcam or camera)

and apply an aging filter that can be selected by a dropdown on the screen. The user should be able to pick different

levels of decades (e.g. 10, 20, 30, 40 years) and then the filter should apply the predicted aging filter on his

face in real-time. The Filter should also apply when the user moves his head.

Technically you may use a frame in the browser window, where the camera stream is shown and the user can see his face.

Then a face detection library should be used, where landmarks of the face are recognized.

With a pretrained model you should be able to apply the aging filter by reference to the landmarks.

The camera data should be fed back to the model making it more accurate.

If possible you should use node.js for backend or local operations, HTML5 and Javascript for the browser Application,

A face detection framework like [login to view URL], clmtrackr or the liking, a machine learning lib like tensorflow.js.

Please provide a solution approach with your offer.


The model should be build upon applying the cGAN like:

[login to view URL]

Compétences : JavaScript, Architecture Logicielle, Machine Learning (ML), Tensorflow, HTML5

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Concernant l'employeur :
( 0 commentaires ) Doerentrup, Germany

Nº du projet : #28292715

25 freelances font une offre moyenne de 1311 € pour ce travail


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