Face detection has been around for ages. Taking a step forward, human emotion displayed by face and felt by brain, captured in either video or image form can be approximated. Human emotion detection is the need of the hour so that modern artificial intelligent systems can emulate and gauge reactions from face. This can be helpful to make informed decisions be it regarding identification of intent, promotion of offers or security related threats. Recognizing emotions from images or video is a trivial task for human eye, but proves to be very challenging for machines and requires many image processing techniques for feature extraction. Several machine learning algorithms are suitable for this job although our group will dry run and select one of those algorithms. The model will give an approximate recognition of the expression and also the percentage of accuracy with it. Any detection or recognition by machine learning requires training algorithm and then testing them on a suitable dataset. So, we will first design the model, then train it using datasets from Kaggle or/and UCL. The language we will be using is python modules used would be OpenCV, tensorflow, Keras and some more basic modules.



Software And Hardware