Other formats:
BibTeX
LaTeX
RIS
@inproceedings{1381785,
author = {Sedmidubský, Jan and Zezula, Pavel and Švec, Jan},
address = {Cham},
booktitle = {21st European Conference on Advances in Databases and Information Systems},
doi = {http://dx.doi.org/10.1007/978-3-319-66917-5_5},
keywords = {subsequence matching; motion capture data; content-based retrieval; similarity measure; segmentation; indexing},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Cham},
isbn = {978-3-319-66916-8},
pages = {59-72},
publisher = {Springer},
title = {Fast Subsequence Matching in Motion Capture Data},
year = {2017}
}
TY - JOUR
ID - 1381785
AU - Sedmidubský, Jan - Zezula, Pavel - Švec, Jan
PY - 2017
TI - Fast Subsequence Matching in Motion Capture Data
PB - Springer
CY - Cham
SN - 9783319669168
KW - subsequence matching
KW - motion capture data
KW - content-based retrieval
KW - similarity measure
KW - segmentation
KW - indexing
N2 - Motion capture data digitally represent human movements by sequences of body configurations in time. Subsequence matching in such spatio-temporal data is difficult as query-relevant motions can vary in lengths and occur arbitrarily in a very long motion. To deal with these problems, we propose a new subsequence matching approach which (1) partitions both short query and long data motion into fixed-size segments that overlap only partly, (2) uses an effective similarity measure to efficiently retrieve data segments that are the most similar to query segments, and (3) localizes the most query-relevant subsequences within extended and merged retrieved segments in a four-step postprocessing phase. The whole retrieval process is effective and fast in comparison with related work. A real-life 68-minute data motion can be searched in about 1s with the average precision of 87.98% for 5-NN queries.
ER -
SEDMIDUBSKÝ, Jan, Pavel ZEZULA and Jan ŠVEC. Fast Subsequence Matching in Motion Capture Data. In \textit{21st European Conference on Advances in Databases and Information Systems}. Cham: Springer, 2017, p.~59-72. ISBN~978-3-319-66916-8. Available from: https://dx.doi.org/10.1007/978-3-319-66917-5\_{}5.
|
