loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Alexandros Kitsikidis 1 ; Kosmas Dimitropoulos 1 ; Stella Douka 2 and Nikos Grammalidis 1

Affiliations: 1 Informatics and Telematics Institute and ITI-CERTH, Greece ; 2 Aristotle University of Thessaloniki, Greece

Keyword(s): Body Motion Analysis and Recognition, Conditional Random Fields, Skeletal Fusion, Dance Analysis.

Abstract: In this paper we present a method for body motion analysis in dance using multiple Kinect sensors. The proposed method applies fusion to combine the skeletal tracking data of multiple sensors in order to solve occlusion and self-occlusion tracking problems and increase the robustness of skeletal tracking. The fused skeletal data is split into five different body parts (torso, left hand, right hand, left leg and right leg), which are then transformed to allow view invariant posture recognition. For each part, a posture vocabulary is generated by performing k-means clustering on a large set of unlabeled postures. Finally, body part postures are combined into body posture sequences and Hidden Conditional Random Fields (HCRF) classifier is used to recognize motion patterns (e.g. dance figures). For the evaluation of the proposed method, Tsamiko dancers are captured using multiple Kinect sensors and experimental results are presented to demonstrate the high recognition accuracy of the pro posed method. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.217.116.183

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Kitsikidis, A.; Dimitropoulos, K.; Douka, S. and Grammalidis, N. (2014). Dance Analysis using Multiple Kinect Sensors. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: IAMICH; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, pages 789-795. DOI: 10.5220/0004874007890795

@conference{iamich14,
author={Alexandros Kitsikidis. and Kosmas Dimitropoulos. and Stella Douka. and Nikos Grammalidis.},
title={Dance Analysis using Multiple Kinect Sensors},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: IAMICH},
year={2014},
pages={789-795},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004874007890795},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: IAMICH
TI - Dance Analysis using Multiple Kinect Sensors
SN - 978-989-758-004-8
IS - 2184-4321
AU - Kitsikidis, A.
AU - Dimitropoulos, K.
AU - Douka, S.
AU - Grammalidis, N.
PY - 2014
SP - 789
EP - 795
DO - 10.5220/0004874007890795
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic