DEV Track Day1 - Detecting Facial Expressions with Azure Machine Learning and Kinect for Windows

This session is about learning how to use Microsoft Azure Machine Learning with the Kinect for Windows in order to detect Facial expressions. This session will cover an introduction to Machine Learning, and different algorithms used to detect data patterns. The algorithms discussed will be nearest neighbor, probabilistic learning, decision trees, and neural networks. It will also cover an introduction to the Kinect for Windows device, such as explaining the features and capabilities of the device and SDK. The session will show basic demos and data coming from the device. The session will then drill down into HD Face and describe the data which is generated from Face and HD Face tracking. Lastly the session will show a demo and provide steps on how to incorporate Azure Machine Learning features into a Windows 8.1 Kinect enabled application to detect facial expressions in real time.

Key topics:
-Learn about what is Microsoft Azure Machine Learning
-Learn about Machine Learning algorithms and how each can help recognize data patterns
-Learn about what is Kinect for Windows
-Learn about the Data that is generated from the Kinect and specifically HD Face
-Learn the steps required to incorporate Microsoft Azure Machine Learning with an Windows 8.1 Kinect enabled application to detect a facial expression