Abstract
Image representation is essential to performance of content-based image retrieval. VLAD has been proved to be superior to BOF. However, hard assignment is utilized in VLAD, which does not consider codeword uncertainty and codeword plausibility. In this paper, each cluster associated to visual word is defined as a hyper-sphere. The radius is denoted as the distance from visual word to the farthest feature point. Spherical soft assignment is proposed to adaptively assign a local feature to close visual words according to corresponding radius. Spherical soft assignment and a descriptor-space soft assignment of state of the art are applied to VLAD. Experiments on multiple datasets demonstrate that the proposed spherical soft assignment can noticeably improve VLAD image representation in image retrieval and be superior to the descriptor-space soft assignment.
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Ai, L., Yu, J., Guan, T. (2012). Spherical Soft Assignment: Improving Image Representation in Content-Based Image Retrieval. In: Lin, W., et al. Advances in Multimedia Information Processing – PCM 2012. PCM 2012. Lecture Notes in Computer Science, vol 7674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34778-8_75
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DOI: https://doi.org/10.1007/978-3-642-34778-8_75
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