Trajectory recognition of moving objects based on hidden Markov model
基于隐马尔可夫模型的运动目标轨迹识别

Using modified hidden Markov model,firstly,aiming at the complex degree of the objects' trajectories in real scene,the models were built for every trajectory pattern,and the training samples were used to get the credible parameters of the model.Finally,the maximum likelihood probability of test samples were computed to all of the trained model,the maximum value was saved and the corresponding model was the recognition result.Then train and recognize the samples clustered,and average recognition rate reach 87.76 % and 94.19% respectively.