The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

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dc.contributor.authorQuek, Francisen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2012-08-24T12:21:01Zen
dc.date.available2012-08-24T12:21:01Zen
dc.date.issued2004-09-18en
dc.date.updated2012-08-24T12:21:01Zen
dc.description.abstractThe catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to “whole gesture” recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationEURASIP Journal on Advances in Signal Processing. 2004 Sep 18;2004(11):769219en
dc.identifier.doihttps://doi.org/10.1155/S1110865704405101en
dc.identifier.urihttp://hdl.handle.net/10919/18975en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderFrancis Quek et al.; licensee BioMed Central Ltd.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleThe Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Senseen
dc.title.serialEURASIP Journal on Advances in Signal Processingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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