Publication

Learning Multi-Modal Dictionaries: Application to Audiovisual Data

Pierre Vandergheynst, Gianluca Monaci, Rémi Gribonval, Philippe Jost
2006
Conference Papers

Abstract

This paper presents a methodology for extracting meaningful synchronous structures from multi-modal signals. Simultaneous processing of multi-modal data can reveal information that is unavailable when handling the sources separately. However, in natural high-dimensional data, the statistical dependencies between modalities are, most of the time, not obvious. Learning fundamental multi-modal patterns is an alternative to classical statistical methods. Typically, recurrent patterns are shift invariant, thus the learning should try to find the best matching filters. We present a new algorithm for iteratively learning multi-modal generating functions that can be shifted at all positions in the signal. The proposed algorithm is applied to audiovisual sequences and it demonstrates to be able to discover underlying structures in the data.

Official source

https://infoscience.epfl.ch/entities/publication/3fb333ea-751f-4e60-9077-6d2e22972ddf

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Pierre Vandergheynst, Gianluca Monaci, Rémi Gribonval, Philippe Jost
2006
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/3fb333ea-751f-4e60-9077-6d2e22972ddf

About this result

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