Similarity Searching in Long Sequences of Motion Capture Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00088023" target="_blank" >RIV/00216224:14330/16:00088023 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-46759-7_21" target="_blank" >http://dx.doi.org/10.1007/978-3-319-46759-7_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-46759-7_21" target="_blank" >10.1007/978-3-319-46759-7_21</a>
Alternative languages
Result language
angličtina
Original language name
Similarity Searching in Long Sequences of Motion Capture Data
Original language description
Motion capture data digitally represent human movements by sequences of body configurations in time. Searching in such spatio-temporal data is difficult as query-relevant motions can vary in lengths and occur arbitrarily in the very long data sequence. There is also a strong requirement on effective similarity comparison as the specific motion can be performed by various actors in different ways, speeds or starting positions. To deal with these problems, we propose a new subsequence matching algorithm which uses a synergy of elastic similarity measure and multi-level segmentation. The idea is to generate a minimum number of overlapping data segments so that there is at least one segment matching an arbitrary subsequence. A non-partitioned query is then efficiently evaluated by searching for the most similar segments in a single level only, while guaranteeing a precise answer with respect to the similarity measure.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of 9th International Conference on Similarity Search and Applications (SISAP 2016), LNCS 9939
ISBN
9783319467580
ISSN
0302-9743
e-ISSN
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Number of pages
15
Pages from-to
271-285
Publisher name
Springer International Publishing AG
Place of publication
Cham (ZG)
Event location
Tokyo, Japan
Event date
Jan 1, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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