Hand Tracking with an Extended Self-Organizing Map

Andreea State; Foti Coleca; Erhardt Barth; Thomas Martinetz

doi:10.1007/978-3-642-35230-0_12

Hand Tracking with an Extended Self-Organizing Map

Andreea State, Foti Coleca, Erhardt Barth, Thomas Martinetz

Institut für Neuro- und Bioinformatik

5 Zitate (Scopus)

Abstract

We introduce an extension of the self-organizing map for performing 3D hand skeleton tracking. We use a range camera for data acquisition and apply a SOM-like learning process within each frame in order to capture the hand pose. Our method uses a topology consisting of 1D and 2D segments for an improved representation of the hand. The proposed algorithm is very efficient and produces good tracking results.

Originalsprache	Englisch
Titel	Advances in Self-Organizing Maps
Redakteure/-innen	Pablo A. Estévez, José C. Príncipe, Pablo Zegers
Seitenumfang	10
Band	Vol. 198
Herausgeber (Verlag)	Springer Berlin Heidelberg
Erscheinungsdatum	2013
Seiten	115-124
ISBN (Print)	978-3-642-35229-4
ISBN (elektronisch)	978-3-642-35230-0
DOIs	https://doi.org/10.1007/978-3-642-35230-0_12
Publikationsstatus	Veröffentlicht - 2013
Veranstaltung	9th Workshop on Self-Organizing Maps - Santiago, Santiago, Chile Dauer: 12.12.2012 → 14.12.2012 http://www.die.uchile.cl/wsom2012/

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10.1007/978-3-642-35230-0_12

http://www.inb.uni-luebeck.de/publications/pdfs/StCoBaMa13.pdf

Weitere Links

https://link.springer.com/chapter/10.1007/978-3-642-35230-0_12

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@inproceedings{fcdedc6196234f7ea5c5e4ac1e9be9ee,

title = "Hand Tracking with an Extended Self-Organizing Map",

abstract = "We introduce an extension of the self-organizing map for performing 3D hand skeleton tracking. We use a range camera for data acquisition and apply a SOM-like learning process within each frame in order to capture the hand pose. Our method uses a topology consisting of 1D and 2D segments for an improved representation of the hand. The proposed algorithm is very efficient and produces good tracking results.",

author = "Andreea State and Foti Coleca and Erhardt Barth and Thomas Martinetz",

year = "2013",

doi = "10.1007/978-3-642-35230-0\_12",

language = "English",

isbn = "978-3-642-35229-4",

volume = "Vol. 198",

series = "Advances in Intelligent Systems and Computing ",

publisher = "Springer Berlin Heidelberg",

pages = "115--124",

editor = "Est{\'e}vez, \{Pablo A. \} and Pr{\'i}ncipe, \{Jos{\'e} C. \} and Zegers, \{Pablo \}",

booktitle = "Advances in Self-Organizing Maps",

note = "9th Workshop on Self-Organizing Maps ; Conference date: 12-12-2012 Through 14-12-2012",

url = "http://www.die.uchile.cl/wsom2012/",

}

State, A, Coleca, F, Barth, E & Martinetz, T 2013, Hand Tracking with an Extended Self-Organizing Map. in PA Estévez, JC Príncipe & P Zegers (Hrsg.), Advances in Self-Organizing Maps. Bd. Vol. 198, Advances in Intelligent Systems and Computing , Bd. Vol. 198, Springer Berlin Heidelberg, S. 115-124, 9th Workshop on Self-Organizing Maps, Santiago, Chile, 12.12.12. https://doi.org/10.1007/978-3-642-35230-0_12

Hand Tracking with an Extended Self-Organizing Map. / State, Andreea; Coleca, Foti; Barth, Erhardt et al.
Advances in Self-Organizing Maps. Hrsg. / Pablo A. Estévez; José C. Príncipe; Pablo Zegers. Band Vol. 198 Springer Berlin Heidelberg, 2013. S. 115-124 (Advances in Intelligent Systems and Computing ; Band Vol. 198).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Hand Tracking with an Extended Self-Organizing Map

AU - State, Andreea

AU - Coleca, Foti

AU - Barth, Erhardt

AU - Martinetz, Thomas

PY - 2013

Y1 - 2013

N2 - We introduce an extension of the self-organizing map for performing 3D hand skeleton tracking. We use a range camera for data acquisition and apply a SOM-like learning process within each frame in order to capture the hand pose. Our method uses a topology consisting of 1D and 2D segments for an improved representation of the hand. The proposed algorithm is very efficient and produces good tracking results.

AB - We introduce an extension of the self-organizing map for performing 3D hand skeleton tracking. We use a range camera for data acquisition and apply a SOM-like learning process within each frame in order to capture the hand pose. Our method uses a topology consisting of 1D and 2D segments for an improved representation of the hand. The proposed algorithm is very efficient and produces good tracking results.

UR - https://link.springer.com/chapter/10.1007/978-3-642-35230-0_12

U2 - 10.1007/978-3-642-35230-0_12

DO - 10.1007/978-3-642-35230-0_12

M3 - Conference contribution

SN - 978-3-642-35229-4

VL - Vol. 198

T3 - Advances in Intelligent Systems and Computing

SP - 115

EP - 124

BT - Advances in Self-Organizing Maps

A2 - Estévez, Pablo A.

A2 - Príncipe, José C.

A2 - Zegers, Pablo

PB - Springer Berlin Heidelberg

T2 - 9th Workshop on Self-Organizing Maps

Y2 - 12 December 2012 through 14 December 2012

ER -

Hand Tracking with an Extended Self-Organizing Map

Abstract

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Dokumente

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