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Scherer, Stefan; Marsella, Stacy C.; Stratou, Giota; Xu, Yuyu; Morbini, Fabrizio; Egan, Alesia; Rizzo, Albert; Morency, Louis-Philippe
Perception Markup Language: Towards a Standardized Representation of Perceived Nonverbal Behaviors Proceedings Article
In: The 12th International Conference on Intelligent Virtual Agents (IVA), Santa Cruz, CA, 2012.
@inproceedings{scherer_perception_2012,
title = {Perception Markup Language: Towards a Standardized Representation of Perceived Nonverbal Behaviors},
author = {Stefan Scherer and Stacy C. Marsella and Giota Stratou and Yuyu Xu and Fabrizio Morbini and Alesia Egan and Albert Rizzo and Louis-Philippe Morency},
url = {http://ict.usc.edu/pubs/Perception%20Markup%20Language-%20Towards%20a%20Standardized%20Representation%20of%20Perceived%20Nonverbal%20Behaviors.pdf},
year = {2012},
date = {2012-09-01},
booktitle = {The 12th International Conference on Intelligent Virtual Agents (IVA)},
address = {Santa Cruz, CA},
abstract = {Modern virtual agents require knowledge about their environment, the interaction itself, and their interlocutors' behavior in order to be able to show appropriate nonverbal behavior as well as to adapt dialog policies accordingly. Recent achievements in the area of automatic behavior recognition and understanding can provide information about the interactants' multimodal nonverbal behavior and subsequently their affective states. In this paper, we introduce a perception markup language (PML) which is a first step towards a standardized representation of perceived nonverbal behaviors. PML follows several design concepts, namely compatibility and synergy, modeling uncertainty, multiple interpretative layers, and extensibility, in order to maximize its usefulness for the research community. We show how we can successfully integrate PML in a fully automated virtual agent system for healthcare applications.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Modern virtual agents require knowledge about their environment, the interaction itself, and their interlocutors' behavior in order to be able to show appropriate nonverbal behavior as well as to adapt dialog policies accordingly. Recent achievements in the area of automatic behavior recognition and understanding can provide information about the interactants' multimodal nonverbal behavior and subsequently their affective states. In this paper, we introduce a perception markup language (PML) which is a first step towards a standardized representation of perceived nonverbal behaviors. PML follows several design concepts, namely compatibility and synergy, modeling uncertainty, multiple interpretative layers, and extensibility, in order to maximize its usefulness for the research community. We show how we can successfully integrate PML in a fully automated virtual agent system for healthcare applications.
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2012
Scherer, Stefan; Marsella, Stacy C.; Stratou, Giota; Xu, Yuyu; Morbini, Fabrizio; Egan, Alesia; Rizzo, Albert; Morency, Louis-Philippe
Perception Markup Language: Towards a Standardized Representation of Perceived Nonverbal Behaviors Proceedings Article
In: The 12th International Conference on Intelligent Virtual Agents (IVA), Santa Cruz, CA, 2012.
Abstract | Links | BibTeX | Tags: Virtual Humans
@inproceedings{scherer_perception_2012,
title = {Perception Markup Language: Towards a Standardized Representation of Perceived Nonverbal Behaviors},
author = {Stefan Scherer and Stacy C. Marsella and Giota Stratou and Yuyu Xu and Fabrizio Morbini and Alesia Egan and Albert Rizzo and Louis-Philippe Morency},
url = {http://ict.usc.edu/pubs/Perception%20Markup%20Language-%20Towards%20a%20Standardized%20Representation%20of%20Perceived%20Nonverbal%20Behaviors.pdf},
year = {2012},
date = {2012-09-01},
booktitle = {The 12th International Conference on Intelligent Virtual Agents (IVA)},
address = {Santa Cruz, CA},
abstract = {Modern virtual agents require knowledge about their environment, the interaction itself, and their interlocutors' behavior in order to be able to show appropriate nonverbal behavior as well as to adapt dialog policies accordingly. Recent achievements in the area of automatic behavior recognition and understanding can provide information about the interactants' multimodal nonverbal behavior and subsequently their affective states. In this paper, we introduce a perception markup language (PML) which is a first step towards a standardized representation of perceived nonverbal behaviors. PML follows several design concepts, namely compatibility and synergy, modeling uncertainty, multiple interpretative layers, and extensibility, in order to maximize its usefulness for the research community. We show how we can successfully integrate PML in a fully automated virtual agent system for healthcare applications.},
keywords = {Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
Modern virtual agents require knowledge about their environment, the interaction itself, and their interlocutors' behavior in order to be able to show appropriate nonverbal behavior as well as to adapt dialog policies accordingly. Recent achievements in the area of automatic behavior recognition and understanding can provide information about the interactants' multimodal nonverbal behavior and subsequently their affective states. In this paper, we introduce a perception markup language (PML) which is a first step towards a standardized representation of perceived nonverbal behaviors. PML follows several design concepts, namely compatibility and synergy, modeling uncertainty, multiple interpretative layers, and extensibility, in order to maximize its usefulness for the research community. We show how we can successfully integrate PML in a fully automated virtual agent system for healthcare applications.