Towards Scalable Retrieval of Human Motion Episodes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00114354" target="_blank" >RIV/00216224:14330/20:00114354 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ISM.2020.00015" target="_blank" >http://dx.doi.org/10.1109/ISM.2020.00015</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ISM.2020.00015" target="_blank" >10.1109/ISM.2020.00015</a>
Alternative languages
Result language
angličtina
Original language name
Towards Scalable Retrieval of Human Motion Episodes
Original language description
With the increasing availability of human motion data captured in the form of 2D/3D skeleton sequences, more complex motion recordings need to be processed. In this paper, we study the problem of similarity-based matching of medium-sized unsegmented skeleton sequences, which we denote as motion episodes. We first apply standard pose-based approaches for matching episodes and analyze their shortcomings. Then, we adopt a recent segment-based approach that transforms episode data into a text-like representation, and apply mature text-processing techniques for matching episodes. We demonstrate that this text-based approach achieves promising results in the terms of both effectiveness and efficiency, and can be further indexed to implement scalable episode retrieval.
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
22nd IEEE International Symposium on Multimedia (ISM)
ISBN
9781728186979
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
49-56
Publisher name
IEEE Computer Society
Place of publication
Washington, DC
Event location
Naples, Italy
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000654273000009