Classification of Poses and Movement Phases

We have focused on the problem of classification of motion frames representing different poses by supervised machine learning and dimensionality reduction techniques. We have extracted motion frames from global database manually, divided them into six different classes and applied classifiers to automatic pose type detection. We have used statistical Bayes, neural network, random forest and Kernel PCA classifiers with wide range of their parameters. We have tried classification on the original data frames and additional reduced their dimensionality by PCA and Kernel PCA methods. We have obtained satisfactory results rated in best case 100 percent of classifiers efficiency.