Please use this identifier to cite or link to this item: https://doi.org/10.1145/1291233.1291335
Title: Annotation of paintings with high-level semantic concepts using transductive inference and ontology-based concept disambiguation
Authors: Leslie, L.
Chua, T.-S. 
Ramesh, J.
Keywords: Concepts ontology
Multi-expert
Ontology-based disambiguation
Paintings
Transductive inference
Issue Date: 2007
Source: Leslie, L.,Chua, T.-S.,Ramesh, J. (2007). Annotation of paintings with high-level semantic concepts using transductive inference and ontology-based concept disambiguation. Proceedings of the ACM International Multimedia Conference and Exhibition : 443-452. ScholarBank@NUS Repository. https://doi.org/10.1145/1291233.1291335
Abstract: Domain-specific knowledge of paintings defines a wide range of concepts for annotation and flexible retrieval of paintings. In this work, we employ the ontology of artistic concepts that includes visual (or atomic) concepts at the intermediate level and high-level concepts at the application level. Visual-level color and brushwork concepts are widely used by art historians to analyze paintings and serve as cues for annotating high-level concepts such as the artist names, painting styles and art periods for paintings. In this research we combine the color and brushwork concepts with low-level features and utilize the transductive inference framework to annotate high-level concepts to the image blocks. In order to resolve conflicting assignments of high-level concepts, we further employ the ontology-based concept disambiguation method and generate image-level annotations. This method performs global optimization of the block-level annotations using the linear constraints extracted from domain knowledge. Our experiments on annotating high-level concepts demonstrate that: a) the use of visual-level concepts significantly improves the accuracy as compared to using low-level features only; and b) the proposed transductive inference framework out-performs the conventional baseline methods and c) the proposed ontology-based disambiguation method generates superior results for several annotation scenarios. Copyright 2007 ACM.
Source Title: Proceedings of the ACM International Multimedia Conference and Exhibition
URI: http://scholarbank.nus.edu.sg/handle/10635/40147
ISBN: 9781595937025
DOI: 10.1145/1291233.1291335
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