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Combining Intra-Image and Inter-Class Semantics for Image Matching

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Definition:Both local (intra-image) and global (inter-class) similarities play complementary roles in image matching and ranking, so a simple linear combination scheme has been experimented with significant performance improvement over single image matching schemes.

Given an image retrieval system, the information need of a user can be modeled as the posterior probability of the set of relevant images R given an expression of the information need in the form of query specification q and an image x in the current database, P(R|q,x). The objective of the system is to return images with high probabilities of relevance to the user.

In Query By Example, P(R|q,x) depends on the similarity between query q and image x. On the other hand, we note that the set of relevant images R does not exist until a query has been specified. However we can construct prior categories of images Ck, k=1, 2, …, M as some prototypical instances of R and compute the memberships of q and xto these prior...

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References

  1. J.N. Kapur and H.K. Kesava, “Entropy Optimization Principles with Applications,” Academic Press, 1992.

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  2. S.E. Robertson and K. Sparck Jones, “Relevance weighting of search terms,” Journal of the American Society for Information Sciences, Vol. 27, 1976, pp. 129–146.

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  3. J.H. Lim, and J.S. Jin, “Combining intra-image and inter-class semantics for consumer image retrieval,” Pattern Recognition, Vol. 38, No. 6, 2005, pp. 847–864.

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© 2006 Springer Science+Business Media, Inc.

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(2006). Combining Intra-Image and Inter-Class Semantics for Image Matching. In: Furht, B. (eds) Encyclopedia of Multimedia. Springer, Boston, MA. https://doi.org/10.1007/0-387-30038-4_27

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