Abstract

This paper presents a projection onto convex sets (POCS)-based semantic image retrieval method and its performance verification. The main contributions of the proposed method are twofold: introduction of nonlinear eigenspace of visual and semantic features into the constraint of the POCS-based semantic image retrieval algorithm and adaptive selection of the annotated images utilized for this algorithm. Then, by combining these two approaches, the semantic features of the query image are successfully estimated, and accurate image retrieval can be expected. Finally, relationship between the performance of the proposed method and the kinds of the kernel functions utilized for the kernel PCA is shown in this paper.

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