Analysis of mood using video

Human uses communications to express their state of mood, usually nonverbal communication like hand gesture, facial expression, tone of voice. However, face is our primitive focus of attention that plays an important role to identify our emotion. Understanding state of mood is beneficial when computer could monitor humans mood and adapt is human-computer interaction for more user-friendly environment. Analysis of Mood using video is an application which read human facial expression and makes a guess of what the user is feeling. We stick to the 6 basic emotion proposed by Ekman (1972): Anger, Disgust, Fear, Happy, Sad, and Surprise. This project will include exploration and building the model to address the accuracy challenge in terms of face feature detection, and classification using Support Vector Machine. In conclusion, the project was successfully designed and implemented from ground-zero to full functionality. We have achieved more than the project was the original goal such that to complete C++ desktop application with facial feature detection, dataset generation, data classification, and lastly mood prediction. In addition, Android application was implemented using Java as the enhancement. It is to reuse the existing native C++ libraries and code while switching platform. This mobile application obtained JNI framework as well as Android NDK that could wrap the previously used native libraries. Another highlight was that simple music function was completed and added into Android application. It served as music therapy which changes its song corresponding to its user's mood.Bachelor of Engineering (Computer Science