Infrared Human Posture Recognition Method Based on Hidden Markov Model

Abstract

The movement of human action recognition technology is the key to human-computer interaction. For the movement of human action recognition problem, this paper has studied the theoretical basis of hidden Markov models including their mathematical background, model definition and hidden Markov model (HMM). After that, we have built the establishment of human action on hidden Markov models and train the model parameters. And this model can effectively target human action classification. Compared with conventional hidden Markov model, the method proposed in this paper to solve the movement of human action recognition problem attempts to establish a model of training data according to the characteristics of human action itself. And according to this, the complex problem is decomposed, thus reducing the computational complexity, to the practical applications to improve system performance results. Through the experiment in the real environment, the experiment show that the model in the practical application can be identification of the different body movement actions by observing human action sequence, matching identification and classification process.