Learning one-to-many mapping functions for audio-visual integrated perception

Jung-Hui Lim; Do-Kwan Oh; Soo-Young Lee

doi:10.1117/12.855241

12 April 2010 Learning one-to-many mapping functions for audio-visual integrated perception

Jung-Hui Lim, Do-Kwan Oh, Soo-Young Lee

Proceedings Volume 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII; 77030E (2010) https://doi.org/10.1117/12.855241
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

In noisy environment the human speech perception utilizes visual lip-reading as well as audio phonetic classification. This audio-visual integration may be done by combining the two sensory features at the early stage. Also, the top-down attention may integrate the two modalities. For the sensory feature fusion we introduce mapping functions between the audio and visual manifolds. Especially, we present an algorithm to provide one-to-many mapping function for the videoto- audio mapping. The top-down attention is also presented to integrate both the sensory features and classification results of both modalities, which is able to explain McGurk effect. Each classifier is separately implemented by the Hidden-Markov Model (HMM), but the two classifiers are combined at the top level and interact by the top-down attention.

Citation Download Citation

Jung-Hui Lim, Do-Kwan Oh, and Soo-Young Lee "Learning one-to-many mapping functions for audio-visual integrated perception", Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 77030E (12 April 2010); https://doi.org/10.1117/12.855241

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KEYWORDS

Associative arrays

Visualization

Video

Sensors

Acoustics

Detection and tracking algorithms

Electronic filtering

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