Real-Time 3D Motion Recognition of Skeleton Animation Data Stream
Jianchao Lv, Shuangjiu Xiao · International Journal of Machine Learning and Computing · 2013
In this paper, a method for real-time 3D motion recognition based on a hierarchical recognition framework is presented.To facilitate the recognition process, motions are divided into three levels by duration and complexity.SVD (Singular Value Decomposition) is used to extract the feature vector of each motion matrix, and SVM(Support Vector Machine) is utilized to do the training and classification of the first level of motion(sub-motion).In motion recognition process, the sequence of recognized candidate sub-motions is analyzed by HMM (Hidden Markov Model) to gain certain robustness, then we recognize the second level of motions by pattern matching in this sequence.Finally a grammar-based motion synthesization is applied using motions as semantic terms to recognize the third level of motions.Experimental results show that the proposed method has high performance in sensitivity, accuracy, specialty and efficiency.