Multimodal Integration for Meeting Group Action Segmentation and Recognition
Type of publication: | Conference paper |
Citation: | zhang-rr-05-31b |
Booktitle: | MLMI |
Year: | 2005 |
Note: | IDIAP-RR 05-31 |
Crossref: | zhang-rr-05-31: |
Abstract: | We address the problem of segmentation and recognition of sequences of multimodal human interactions in meetings. These interactions can be seen as a rough structure of a meeting, and can be used either as input for a meeting browser or as a first step towards a higher semantic analysis of the meeting. A common lexicon of multimodal group meeting actions, a shared meeting data set, and a common evaluation procedure enable us to compare the different approaches. We compare three different multimodal feature sets and four modelling infrastructures: a higher semantic feature approach, multi-layer HMMs, a multi-stream DBN, as well as a multi-stream mixed-state DBN for disturbed data. |
Userfields: | ipdmembership={vision}, |
Keywords: | |
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Idiap |
Authors | |
Added by: | [UNK] |
Total mark: | 0 |
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