ImageSaker: A Semantic-based Image Retrieval System Refining with Concept Model
نویسندگان
چکیده
In this demonstration, a two-level system for semantic-based image retrieval is proposed. To overcome the shortcoming of the traditional retrieval system, we present a novel method which can provide effective retrieval result in a short time. Firstly, it uses surrounding text to get a related candidate image set. Secondly, a semantic network is used to map the keyword to one of concept models which describe the statistical character of semantic relevant images. Afterwards, the system refines the small image set using the model to get more accurate retrieval result. In order to train concept models, we propose an improved method based on SVM (Support Vector Machine). Experiments show that the proposed method is effective for WWW image retrieval.
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