A Real-Time Annotation of Motion Data Streams

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00094976" target="_blank" >RIV/00216224:14330/17:00094976 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1109/ISM.2017.29" target="_blank" >http://dx.doi.org/10.1109/ISM.2017.29</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISM.2017.29" target="_blank" >10.1109/ISM.2017.29</a>

Result language

angličtina

Original language name

A Real-Time Annotation of Motion Data Streams

Original language description

Current motion-capture technologies produce continuous streams of 3D human joint trajectories. One of the challenges is to automatically annotate such streams of complex spatio-temporal data in real time. In this paper, we propose an efficient approach to label motion stream data in real time with a limited usage of main memory. Based on a set of user-defined motion profiles, each of them specified by multiple representative samples, the currently visible part of an input motion stream is processed by identifying a moderate number of segments of various lengths. These segments are compared to the profiles to measure their similarity. The segments having a high similarity to a given motion profile are annotated with the corresponding label. The proposed approach performs fast, allows profiles to be dynamically changed at runtime, and does not require any learning procedure, in comparison with existing solutions evaluated on real-life data.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA16-18889S" target="_blank" >GA16-18889S: Big Data Analytics for Unstructured Data</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

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

Article name in the collection

19th IEEE International Symposium on Multimedia

ISBN

9781538629376

ISSN

—

e-ISSN

—

Number of pages

8

Pages from-to

154-161

Publisher name

IEEE Computer Society

Place of publication

Neuveden

Event location

Taichung, Taiwan

Event date

Jan 1, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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