Motion Stream Segmentation and Recognition by Classification
This paper proposes a classification-based approach to segmenting and recognizing patterns in motion signals. Feature vectors are extracted based on singular value decomposition (SVD) for classification. Multi-class support vector machine (SVM) classifiers with class probability estimates are explored for segmenting and recognizing motion streams. Experiments show that the proposed approach can find patterns in the multi-attribute motion streams with high accuracy