UROP1100_Emotion_Recognition

The research aims to find a best algorithm to complete the real-time emotion recognition task on the wearable devices such as mobile phone and google glasses. In this research, we first design several machine learning emotion recognition algorithms based on some existing facial recognition algorithm and test them on some famous emotion dataset such as CK+ and Yale dataset to find the best algorithm. Then we try to implement it in android system to see whether it also works well in real-time recognition.

The Emotion folder contains the emotion labels of CK+ dataset

The Landmark folder contains the emotion labels of CK+ dataset

The Ipynb folder contains the code of testing the algorithm in CK+ dataset

More information about the project and the designed algorithms can be found in the UROP1100_Report.pdf