Face Recognition iOS
An entertaining mobile application uses a neural network for facial recognition.
Facial recognition works by measuring the unique characteristics of a user’s face and then comparing the source data with an existing database of entries. First, the app detects the picture frame with the user’s face. Then the neural network detemines user’s face landmarks, which are a 128-dimensional array. Then the application determines the similarity between the input face landmarks and the landmarks of other users, stored in the database.
The iOS Face Recognition app uses a cloud server as a back-end. This allows for increasing the face recognition speed, delivering the results in real-time.
DB Best utilized Swift to build the iOS application. We leveraged an open-source dlib library and two already trained neural networks to find the faces on the pictures and extract the face landmarks.
Be sure to check the related blog post and the video above to learn more about using neural networks to create face recognition applications.
- iOS client development
- Back-end and front-end development
- Software design and architecture
- Quality assurance
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Some cutting-edge technologies were used in the development of this app.
A custom emoji keyboard designed by Niall Horan himself.