Matrix computations (3rd ed.)
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Semantic representation: search and mining of multimedia content
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Rotation invariant distance measures for trajectories
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Probability Estimates for Multi-class Classification by Pairwise Coupling
The Journal of Machine Learning Research
Phrase structure detection in dance
Proceedings of the 12th annual ACM international conference on Multimedia
Segmentation and recognition of multi-attribute motion sequences
Proceedings of the 12th annual ACM international conference on Multimedia
A PCA-based similarity measure for multivariate time series
Proceedings of the 2nd ACM international workshop on Multimedia databases
A similarity measure for motion stream segmentation and recognition
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
Real-time classification of variable length multi-attribute motions
Knowledge and Information Systems
Applications of support vector machines to speech recognition
IEEE Transactions on Signal Processing
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Perceptually consistent example-based human motion retrieval
Proceedings of the 2009 symposium on Interactive 3D graphics and games
Blind robust watermarking of 3d motion data
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A group of novel approaches and a toolkit for motion capture data reusing
Multimedia Tools and Applications
Efficacy of gesture for communication among humanoid robots by fuzzy inference method
International Journal of Computational Vision and Robotics
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Three dimensional human motions recorded by motion capture and hand gestures recorded by using data gloves generate variable-length data streams. These data streams usually have dozens of attributes, and have different variations for similar motions. To segment and recognize motion streams, a classification-based approach is proposed in this paper. Classification feature vectors are extracted by utilizing singular value decompositions (SVD) of motion data. The extracted feature vectors capture the dominating geometric structures of motion data as revealed by SVD. Multi-class support vector machine (SVM) classifiers with class probability estimates are explored for classifying the feature vectors in order to segment and recognize motion streams. Experiments show that the proposed approach can find patterns in motion data streams with high accuracy.