An Evaluation Study of Recognizing Conducting Gesture Using Computational Intelligence Techniques

Humans express themselves through movements. These movements range from a simple hand gesture while they are talking to the complex movements of a dancer. Musicians are highly trained artists that use their movements to invoke artistic purposes or make different sounds. This paper explores the attempt to recognize and understand the gesture of a conductor via computational means. With the ubiquitous availability of mobile phones, these devices are ideal in being utilized as tools for capturing the movement of our subject. We have implemented two computational intelligence algorithms to recognize the gesture of a conductor: a) Hidden Markov Model and b) Feed-Forward Neural Network. This paper will present the preliminary findings of the project.