A Multi-class Kernel Alignment Method for Image Collection Summarization
Identifieur interne : 003A29 ( Main/Exploration ); précédent : 003A28; suivant : 003A30A Multi-class Kernel Alignment Method for Image Collection Summarization
Auteurs : Jorge E. Camargo [Colombie] ; Fabio A. González [Colombie]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: This paper proposes a method for involving domain knowledge in the construction of summaries of large collections of images. This is accomplished by using a multi-class kernel alignment strategy in order to learn a kernel function that incorporates domain knowledge (class labels). The kernel function is the basis of a clustering algorithm that generates a subset, the summary, of the image collection. The method was tested with a subset of the Corel image collection using a summarization quality measure based on information theory. Experimental results show that it is possible to improve the quality of the summary when domain knowledge is involved.
Url:
DOI: 10.1007/978-3-642-10268-4_64
Affiliations:
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