/BiometricSystemsCognitiveServices

Biometric Systems exam project. Perform near-real-time analysis on faces (emotions, gender, age, etc.), taken from a live video stream with Azure Cognitive Services and AWS Rekognition and Kinesis.

Primary LanguageC#MIT LicenseMIT

Biometric Systems Project

This project is made by students of Sapienza, University of Rome, enrolled in MSc in Engineering in Computer Science: Chiara Navarra, Federico Guidi, Roberto Falconi and Stefan Clinciu, for Biometric Systems course.

Get your own Cognitive Services API keys on microsoft.com/cognitive, for video frame analysis the applicable APIs are Computer Vision API and Face API.
Open the sample in Visual Studio, build and run the application inserting the API keys in the settings using IIS (Internet Information Services)

References

OpenCV: https://opencv.org/
Microsoft Azure Cognitive Services: https://azure.microsoft.com/en-us/services/cognitive-services/
Computer Vision: https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/
Custom Vision API: https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/
Face API: https://azure.microsoft.com/en-us/services/cognitive-services/face/
Face Detection: https://docs.microsoft.com/bs-latn-ba/azure/cognitive-services/face/face-api-how-to-topics/howtodetectfacesinimage

Useful Links

GitHub:
https://github.com/ChiaraNavarra
https://github.com/FedericoGuidi
https://github.com/RobertoFalconi
https://github.com/Clincius
LinkedIn:
https://www.linkedin.com/in/chiaranavarra/
https://www.linkedin.com/in/federico-guidi/
https://www.linkedin.com/in/roberto-falconi/
https://www.linkedin.com/in/stefan-clinciu-7421b2a6/
SlideShare:
https://www.slideshare.net/RobertoFalconi4
https://www.slideshare.net/FedericoGuidi5