Real Time Face Detection on Android with Firebase

Tuesday 4:30 pm, Room 1
All

About This Talk

Langauge : English

Firebase ML Kit is the perfect place to begin your journey into Machine Learning. Firebase ML Kit offers simple SDKs to allow you to get up and running quickly and effectively, without having to get too deep into the theory of ML and TensorFlow (without excluding the possibility of using it either). This presentation is designed to take you on a beginners journey into Facial Recognition, to demonstrate just how simple yet powerful the stock Firebase ML Kit really is.

Takeaways

By the end of the presentation you will have learned how to get setup in Firebase, how to take a photo or image, detect faces within it and alter them, then finally, how to analyse your camera feed detect faces in real time and overlay a graphic of some kind to parts of the faces - maybe a moustache or rabbit teeth?

Reasoning

Firebase is making is easier and easier to start using technology that, 5 years ago, was simply not accessible to the average developer. Now, SDKs that provide simple API’s for face detection, text detection, speech recognition (and recently even smart replies!) are becoming freely available in offline mode. This opens many doors for both hobbyists, startups and enterprise alike. Demonstrating this potential is crucial to getting this technology into the hands of as many young developers as possible so that the most creative minds are not hindered by something so trivial as access.

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Nick Skelton

Nick is a Google Developer Expert from Australia (although he lives in Germany) and Freelance Android Developer. He works full time remote from Munich as an Android Developer in a team that is spread all over Europe. He has given talks at Droidcon Madrid and Krakow as well as UaMobi.Tech Ukraine on topics such as Android Security, Continuous Integration, Kotlin Adoption and Firebase. He is also a co-organiser of the Kotlin Meetup in Munich, Germany where he gives lightning talks while eating and drinking pizza (not at the same time).

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