Motion Words: A Text-like Representation of 3D Skeleton Sequences
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00114026" target="_blank" >RIV/00216224:14330/20:00114026 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-45439-5_35" target="_blank" >http://dx.doi.org/10.1007/978-3-030-45439-5_35</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-45439-5_35" target="_blank" >10.1007/978-3-030-45439-5_35</a>
Alternative languages
Result language
angličtina
Original language name
Motion Words: A Text-like Representation of 3D Skeleton Sequences
Original language description
There is a growing amount of human motion data captured as a continuous 3D skeleton sequence without any information about its semantic partitioning. To make such unsegmented and unlabeled data efficiently accessible, we propose to transform them into a text-like representation and employ well-known text retrieval models. Specifically, we partition each motion synthetically into a sequence of short segments and quantize the segments into motion words, i.e. compact features with similar characteristics as words in text documents. We introduce several quantization techniques for building motion-word vocabularies and propose application-independent criteria for assessing the vocabulary quality. We verify these criteria on two real-life application scenarios.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/GA19-02033S" target="_blank" >GA19-02033S: Searching, Mining, and Annotating Human Motion Streams</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
42nd European Conference on Information Retrieval (ECIR)
ISBN
9783030454388
ISSN
0302-9743
e-ISSN
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Number of pages
15
Pages from-to
527-541
Publisher name
Springer
Place of publication
Cham
Event location
Lisbon, Portugal
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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