A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario

Tobias Rehrl; Jürgen Gast; Nikolaus Theißing; Alexander Bannat; Dejan Arsić; Frank Wallhoff; Gerhard Rigoll; Christoph Mayer; Bernd Radig

doi:10.1109/CVPRW.2010.5543751

A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario

Tobias Rehrl, Jürgen Gast, Nikolaus Theißing, Alexander Bannat, Dejan Arsić, Frank Wallhoff, Gerhard Rigoll, Christoph Mayer, Bernd Radig

Technische Universität München

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

1 Zitat (Scopus)

Abstract

This paper introduces our research platform for enabling a multimodal Human-Robot Interaction scenario as well as our research vision: approaching problems in a holistic way to realize this scenario. However, in this paper the main focus is laid on the image processing domain, where our vision has been realized by combining particle tracking and Dynamic Bayesian Network classification in a unified Graphical Model. This combination allows for enhancing the tracking process by an adaptive motion model realized via a Dynamic Bayesian Network modeling several motion classes. The Graphical Model provides a direct integration of the classification step in the tracking process. First promising results show the potential of the approach.

Originalsprache	Englisch
Titel	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Seiten	17-23
Seitenumfang	7
DOIs	https://doi.org/10.1109/CVPRW.2010.5543751
Publikationsstatus	Veröffentlicht - 2010
Veranstaltung	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 - San Francisco, CA, USA/Vereinigte Staaten Dauer: 13 Juni 2010 → 18 Juni 2010

Publikationsreihe

Name	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

Konferenz

Konferenz	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Land/Gebiet	USA/Vereinigte Staaten
Ort	San Francisco, CA
Zeitraum	13/06/10 → 18/06/10

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10.1109/CVPRW.2010.5543751

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Rehrl, T., Gast, J., Theißing, N., Bannat, A., Arsić, D., Wallhoff, F., Rigoll, G., Mayer, C., & Radig, B. (2010). A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 (S. 17-23). Artikel 5543751 (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010). https://doi.org/10.1109/CVPRW.2010.5543751

Rehrl, Tobias ; Gast, Jürgen ; Theißing, Nikolaus et al. / A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010. 2010. S. 17-23 (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010).

@inproceedings{eb9558b1df484b54bfbc6ba41d1e8625,

title = "A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario",

abstract = "This paper introduces our research platform for enabling a multimodal Human-Robot Interaction scenario as well as our research vision: approaching problems in a holistic way to realize this scenario. However, in this paper the main focus is laid on the image processing domain, where our vision has been realized by combining particle tracking and Dynamic Bayesian Network classification in a unified Graphical Model. This combination allows for enhancing the tracking process by an adaptive motion model realized via a Dynamic Bayesian Network modeling several motion classes. The Graphical Model provides a direct integration of the classification step in the tracking process. First promising results show the potential of the approach.",

author = "Tobias Rehrl and J{\"u}rgen Gast and Nikolaus Thei{\ss}ing and Alexander Bannat and Dejan Arsi{\'c} and Frank Wallhoff and Gerhard Rigoll and Christoph Mayer and Bernd Radig",

year = "2010",

doi = "10.1109/CVPRW.2010.5543751",

language = "English",

isbn = "9781424470297",

series = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010",

pages = "17--23",

booktitle = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010",

note = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 ; Conference date: 13-06-2010 Through 18-06-2010",

}

Rehrl, T, Gast, J, Theißing, N, Bannat, A, Arsić, D, Wallhoff, F, Rigoll, G, Mayer, C & Radig, B 2010, A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010., 5543751, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010, S. 17-23, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010, San Francisco, CA, USA/Vereinigte Staaten, 13/06/10. https://doi.org/10.1109/CVPRW.2010.5543751

A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario. / Rehrl, Tobias; Gast, Jürgen; Theißing, Nikolaus et al.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010. 2010. S. 17-23 5543751 (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010).

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

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AU - Rehrl, Tobias

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AU - Theißing, Nikolaus

AU - Bannat, Alexander

AU - Arsić, Dejan

AU - Wallhoff, Frank

AU - Rigoll, Gerhard

AU - Mayer, Christoph

AU - Radig, Bernd

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AB - This paper introduces our research platform for enabling a multimodal Human-Robot Interaction scenario as well as our research vision: approaching problems in a holistic way to realize this scenario. However, in this paper the main focus is laid on the image processing domain, where our vision has been realized by combining particle tracking and Dynamic Bayesian Network classification in a unified Graphical Model. This combination allows for enhancing the tracking process by an adaptive motion model realized via a Dynamic Bayesian Network modeling several motion classes. The Graphical Model provides a direct integration of the classification step in the tracking process. First promising results show the potential of the approach.

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Rehrl T, Gast J, Theißing N, Bannat A, Arsić D, Wallhoff F et al. A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010. 2010. S. 17-23. 5543751. (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010). doi: 10.1109/CVPRW.2010.5543751

A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario

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