Exploiting the SVM constraints in NMF with application in eating and drinking activity recognition | IEEE Conference Publication | IEEE Xplore

Exploiting the SVM constraints in NMF with application in eating and drinking activity recognition


Abstract:

A novel method is introduced for exploiting the support vector machine constraints in nonnegative matrix factorization. The notion of the proposed method is to find the p...Show More

Abstract:

A novel method is introduced for exploiting the support vector machine constraints in nonnegative matrix factorization. The notion of the proposed method is to find the projection matrix that projects the data to a low-dimensional space so that the data projections between the two classes are separated with maximum margin. Experiments were performed for the task of eating and drinking activity classification. Experimental results showed that the proposed method achieves better classification performance than the state of the art nonnegative matrix factorization and discriminant nonnegative matrix factorization followed by support vector machines classification.
Date of Conference: 15-18 September 2013
Date Added to IEEE Xplore: 13 February 2014
Electronic ISBN:978-1-4799-2341-0

ISSN Information:

Conference Location: Melbourne, VIC, Australia

References

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