@inproceedings{c20b115d47cc485a94735a481a2e8b47,
title = "A novel indexing approach for efficient and fast similarity search of captured motions",
abstract = "Indexing of motion data is important for quickly searching similar motions for sign language recognition and gait analysis and rehabilitation. This paper proposes a simple and efficient tree structure for indexing motion data with dozens of attributes. Feature vectors are extracted for indexing by using singular value decomposition (SVD) properties of motion data matrices. By having similar motions with large variations indexed together, searching for similar motions of a query needs only one node traversal at each tree level, and only one feature needs to be considered at one tree level. Experiments show that the majority of irrelevant motions can be pruned while retrieving all similar motions, and one traversal of the indexing tree takes only several microseconds with the existence of motion variations.",
author = "Chuanjun Li and B. Prabhakaran",
year = "2006",
doi = "10.1007/11731139\_79",
language = "English",
isbn = "3540332065",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "689--698",
booktitle = "Advances in Knowledge Discovery and Data Mining - 10th Pacific-Asia Conference, PAKDD 2006, Proceedings",
note = "10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006 ; Conference date: 09-04-2006 Through 12-04-2006",
}