Similarity Search in 3D Human Motion Data

D 2019

Similarity Search in 3D Human Motion Data

SEDMIDUBSKÝ, Jan a Pavel ZEZULA

Základní údaje

Originální název

Similarity Search in 3D Human Motion Data

Autoři

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

Vydání

New York, NY, USA, International Conference on Multimedia Retrieval (ICMR), od s. 5-6, 2 s. 2019

Nakladatel

ACM

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10200 1.2 Computer and information sciences

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Kód RIV

RIV/00216224:14330/19:00107369

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4503-6765-3

DOI

http://dx.doi.org/10.1145/3323873.3326589

UT WoS

000482188900003

Klíčová slova anglicky

motion capture data;3D skeleton sequence;similarity search;subsequence matching;annotation;action detection;stream processing

Štítky

DISA

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 15. 4. 2020 10:23, doc. RNDr. Jan Sedmidubský, Ph.D.

Anotace

V originále

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.

Návaznosti

GA19-02033S, projekt VaV

Název: Vyhledávání, analytika a anotace datových toků lidských pohybů

Investor: Grantová agentura ČR, Searching, Mining, and Annotating Human Motion Streams

Citovat

SEDMIDUBSKÝ, Jan a Pavel ZEZULA. Similarity Search in 3D Human Motion Data. Online. In International Conference on Multimedia Retrieval (ICMR). New York, NY, USA: ACM, 2019, s. 5-6. ISBN 978-1-4503-6765-3. Dostupné z: https://dx.doi.org/10.1145/3323873.3326589.

@inproceedings{1525456,
   author = {Sedmidubský, Jan and Zezula, Pavel},
   address = {New York, NY, USA},
   booktitle = {International Conference on Multimedia Retrieval (ICMR)},
   doi = {http://dx.doi.org/10.1145/3323873.3326589},
   keywords = {motion capture data;3D skeleton sequence;similarity search;subsequence matching;annotation;action detection;stream processing},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {New York, NY, USA},
   isbn = {978-1-4503-6765-3},
   pages = {5-6},
   publisher = {ACM},
   title = {Similarity Search in 3D Human Motion Data},
   year = {2019}
}

TY  - JOUR
ID  - 1525456
AU  - Sedmidubský, Jan - Zezula, Pavel
PY  - 2019
TI  - Similarity Search in 3D Human Motion Data
PB  - ACM
CY  - New York, NY, USA
SN  - 9781450367653
KW  - motion capture data;3D skeleton sequence;similarity search;subsequence matching;annotation;action detection;stream processing
N2  - 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.
ER  -

SEDMIDUBSKÝ, Jan a Pavel ZEZULA. Similarity Search in 3D Human Motion Data. Online. In \textit{International Conference on Multimedia Retrieval (ICMR)}. New York, NY, USA: ACM, 2019, s.~5-6. ISBN~978-1-4503-6765-3. Dostupné z: https://dx.doi.org/10.1145/3323873.3326589.

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