Similarity Search in 3D Human Motion Data

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Similarity Search in 3D Human Motion Data

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Similarity Search in 3D Human Motion Data

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/GA19-02033S" target="_blank" >GA19-02033S: Vyhledávání, analytika a anotace datových toků lidských pohybů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

International Conference on Multimedia Retrieval (ICMR)

ISBN

9781450367653

ISSN

—

e-ISSN

—

Počet stran výsledku

2

Strana od-do

5-6

Název nakladatele

ACM

Místo vydání

New York, NY, USA

Místo konání akce

Ottawa, Canada

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000482188900003