Similarity Search in 3D Human Motion Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00107369" target="_blank" >RIV/00216224:14330/19:00107369 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/3323873.3326589" target="_blank" >http://dx.doi.org/10.1145/3323873.3326589</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3323873.3326589" target="_blank" >10.1145/3323873.3326589</a>
Alternative languages
Result language
angličtina
Original language name
Similarity Search in 3D Human Motion Data
Original language description
Motion capture technologies can digitize human movements into a discrete sequence of 3D skeletons. Such spatio-temporal data have a great application potential in many fields, ranging from computer animation, through security and sports to medicine, but their computerized processing is a difficult problem. The objective of this tutorial is to explain fundamental principles and technologies designed for searching, subsequence matching, classification and action detection in the 3D human motion data. These operations inherently require the concept of similarity to determine the degree of accordance between pairs of 3D skeleton sequences. Such similarity can be modeled using a generic approach of metric space by extracting effective deep features and comparing them by efficient distance functions. The metric-space approach also enables applying traditional index structures to efficiently access large datasets of skeleton sequences. We demonstrate the functionality of selected motion-processing operations by interactive web applications.
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
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
International Conference on Multimedia Retrieval (ICMR)
ISBN
9781450367653
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
5-6
Publisher name
ACM
Place of publication
New York, NY, USA
Event location
Ottawa, Canada
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000482188900003