Searching for Variable-Speed Motions in Long Sequences of
Motion Capture Data

J 2019

Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data

SEDMIDUBSKÝ, Jan, Petr ELIÁŠ a Pavel ZEZULA

Základní údaje

Originální název

Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data

Autoři

SEDMIDUBSKÝ, Jan (203 Česká republika, garant, domácí), Petr ELIÁŠ (203 Česká republika, domácí) a Pavel ZEZULA (203 Česká republika, domácí)

Vydání

Information Systems, 2019, 0306-4379

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 2.466

Kód RIV

RIV/00216224:14330/19:00107162

Organizační jednotka

Fakulta informatiky

DOI

http://dx.doi.org/10.1016/j.is.2018.04.002

UT WoS

000454964800012

Klíčová slova anglicky

Content-based retrieval;Motion capture data;Subsequence matching;Speed-invariant retrieval;Similarity measure;Hierarchical segmentation;Indexing

Štítky

DISA

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 16. 4. 2019 07:35, doc. RNDr. Jan Sedmidubský, Ph.D.

Anotace

V originále

Motion capture data digitally represent human movements by sequences of body configurations in time. Subsequence searching in long sequences of such spatio-temporal data is difficult as query-relevant motions can vary in execution speeds and styles and can occur anywhere in a very long data sequence. To deal with these problems, we employ a fast and effective similarity measure that is elastic. The property of elasticity enables matching of two overlapping but slightly misaligned subsequences with a high confidence. Based on the elasticity, the long data sequence is partitioned into overlapping segments that are organized in multiple levels. The number of levels and sizes of overlaps are optimized to generate a modest number of segments while being able to trace an arbitrary query. In a retrieval phase, a query is always represented as a single segment and fast matched against segments within a relevant level without any costly post-processing. Moreover, visiting adjacent levels makes possible subsequence searching of time-warped (i.e., faster or slower executed) queries. To efficiently search on a large scale, segment features can be binarized and segmentation levels independently indexed. We experimentally demonstrate effectiveness and efficiency of the proposed approach for subsequence searching on a real-life dataset.

Návaznosti

GA16-18889S, projekt VaV

Název: Analytika pro velká nestrukturovaná data (Akronym: Big Data Analytics for Unstructured Data)

Investor: Grantová agentura ČR, Big Data Analytics for Unstructured Data

Citovat

SEDMIDUBSKÝ, Jan, Petr ELIÁŠ a Pavel ZEZULA. Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data. Information Systems. 2019, roč. 80, February, s. 148-158. ISSN 0306-4379. Dostupné z: https://dx.doi.org/10.1016/j.is.2018.04.002.

@article{1413841,
   author = {Sedmidubský, Jan and Eliáš, Petr and Zezula, Pavel},
   article_number = {February},
   doi = {http://dx.doi.org/10.1016/j.is.2018.04.002},
   keywords = {Content-based retrieval;Motion capture data;Subsequence matching;Speed-invariant retrieval;Similarity measure;Hierarchical segmentation;Indexing},
   language = {eng},
   issn = {0306-4379},
   journal = {Information Systems},
   title = {Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data},
   url = {http://dx.doi.org/10.1016/j.is.2018.04.002},
   volume = {80},
   year = {2019}
}

TY  - JOUR
ID  - 1413841
AU  - Sedmidubský, Jan - Eliáš, Petr - Zezula, Pavel
PY  - 2019
TI  - Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data
JF  - Information Systems
VL  - 80
IS  - February
SP  - 148-158
EP  - 148-158
SN  - 03064379
KW  - Content-based retrieval;Motion capture data;Subsequence matching;Speed-invariant retrieval;Similarity measure;Hierarchical segmentation;Indexing
UR  - http://dx.doi.org/10.1016/j.is.2018.04.002
L2  - http://dx.doi.org/10.1016/j.is.2018.04.002
N2  - Motion capture data digitally represent human movements by sequences of body configurations in time. Subsequence searching in long sequences of such spatio-temporal data is difficult as query-relevant motions can vary in execution speeds and styles and can occur anywhere in a very long data sequence. To deal with these problems, we employ a fast and effective similarity measure that is elastic. The property of elasticity enables matching of two overlapping but slightly misaligned subsequences with a high confidence. Based on the elasticity, the long data sequence is partitioned into overlapping segments that are organized in multiple levels. The number of levels and sizes of overlaps are optimized to generate a modest number of segments while being able to trace an arbitrary query. In a retrieval phase, a query is always represented as a single segment and fast matched against segments within a relevant level without any costly post-processing. Moreover, visiting adjacent levels makes possible subsequence searching of time-warped (i.e., faster or slower executed) queries. To efficiently search on a large scale, segment features can be binarized and segmentation levels independently indexed. We experimentally demonstrate effectiveness and efficiency of the proposed approach for subsequence searching on a real-life dataset.
ER  -

SEDMIDUBSKÝ, Jan, Petr ELIÁŠ a Pavel ZEZULA. Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data. \textit{Information Systems}. 2019, roč.~80, February, s.~148-158. ISSN~0306-4379. Dostupné z: https://dx.doi.org/10.1016/j.is.2018.04.002.

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