Visual Ontology Construction for Digitized Art Image Retrieval |
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Authors: | Email author" target="_blank">Shu-Qiang?JiangEmail author Jun?Du Qing-Ming?Huang Tie-Jun?Huang Wen?Gao |
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Affiliation: | 1 Digital Media Lab, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, P.R. China; 2 Research Center of Digital Media, Graduate School of the Chinese Academy of Sciences, Beijing 100049, P.R. China |
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Abstract: | Current investigations on visual information retrieval are generally content-based methods. The significant difference between
similarity in low-level features and similarity in high-level semantic meanings is still a major challenge in the area of
image retrieval. In this work, a scheme for constructing visual ontology to retrieve art images is proposed. The proposed
ontology describes images in various aspects, including type & style, objects and global perceptual effects. Concepts in the
ontology could be automatically derived. Various art image classification methods are employed based on low-level image features.
Non-objective semantics are introduced, and how to express these semantics is given. The proposed ontology scheme could make
users more naturally find visual information and thus narrows the “semantic gap”. Experimental implementation demonstrates
its good potential for retrieving art images in a human-centered manner.
Supported by China-American Digital Academic Library (CADAL) project, partially supported by the Research Project on Context-Based
Multiple Digital Media Semantic Organization and System Development (Grant No. op2004001); and the One-Hundred Talents Plan
of CAS (Grant No. m2041). |
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Keywords: | ontology design image/video retrieval image database |
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