Indexing the Distance: An Efficient Method to KNN Processing
Proceedings of the 27th International Conference on Very Large Data Bases
Video Sequence Similarity Matching
MINAR '98 Proceedings of the IAPR International Workshop on Multimedia Information Analysis and Retrieval
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
3D motion retrieval with motion index tree
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
Automated extraction and parameterization of motions in large data sets
ACM SIGGRAPH 2004 Papers
Indexing of variable length multi-attribute motion data
Proceedings of the 2nd ACM international workshop on Multimedia databases
A system for analyzing and indexing human-motion databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Multilevel Distance-Based Index Structure for Multivariate Time Series
TIME '05 Proceedings of the 12th International Symposium on Temporal Representation and Reasoning
Efficient content-based retrieval of motion capture data
ACM SIGGRAPH 2005 Papers
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Segmentation and recognition of motion streams by similarity search
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Computer
Indexing large human-motion databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
On convergence properties of the em algorithm for gaussian mixtures
Neural Computation
Semantic quantization of 3D human motion capture data through spatial-temporal feature extraction
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Hierarchical indexing structure for 3d human motions
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
On spatial quantization of color images
IEEE Transactions on Image Processing
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3D human motion capture is a form of multimedia data that is widely used in entertainment as well as medical fields (such as orthopedics, physical medicine, and rehabilitation where gait analysis is needed). These applications typically create large repositories of motion capture data and need efficient and accurate content-based retrieval techniques. 3D motion capture data is in the form of multidimensional time-series data. To reduce the dimensions of human motion data while maintaining semantically important features, we quantize human motion data by extracting spatio-temporal features through SVD and translate them onto a symbolic sequential representation through our proposed sGMMEM (semantic Gaussian Mixture Modeling with EM). In order to handle variations in motion capture data due to human body characteristics and speed of motion, we transform the semantically quantized values into a histogram representation. This representation is used as a signature for classification and similarity-based retrieval. We achieved good classification accuracies for “coarse” human motion categories (such as walking 92.85%, run 91.42%, and jump 94.11%) and even for subtle categories (such as dance 89.47%, laugh 83.33%, basketball signal 85.71%, golf putting 80.00%). Experiments also demonstrated that the proposed approach outperforms earlier techniques such as the wMSV (weighted Motion Singular Vector) approach and LB_Keogh method.