Similarity Search in 3D Human Motion Data

D 2019

Similarity Search in 3D Human Motion Data

SEDMIDUBSKÝ, Jan and Pavel ZEZULA

Basic information

Original name

Similarity Search in 3D Human Motion Data

Authors

SEDMIDUBSKÝ, Jan (203 Czech Republic, guarantor, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution)

Edition

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

Publisher

ACM

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/19:00107369

Organization unit

Faculty of Informatics

ISBN

978-1-4503-6765-3

DOI

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

UT WoS

000482188900003

Keywords in English

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

Abstract

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.

Links

GA19-02033S, research and development project

Name: Vyhledávání, analytika a anotace datových toků lidských pohybů

Investor: Czech Science Foundation

Citovat

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

Detailed Information on Publication Record