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Handling Significant Scale Difference for Object Retrieval in a Supermarket

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Authors

Zhang, Yuhang
Wang, Lei
Hartley, Richard
Li, Hongdong

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Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

We propose an object retrieval application which can retrieve user specified objects from a big supermarket. Significant and unpredictable scale difference between the query and the database image is the major obstacle encountered. The widely used local invariant features show their deficiency in such an occasion. To improve the situation, we first design a new weighting scheme which can assess the repeatability of local features against scale variance. Also, another method which deals with scale difference through retrieving a query under multiple scales is also developed. Our methods have been tested on a real image database collected from a local supermarket and outperform the existing local invariant feature based image retrieval approaches. A new spatial check method is also briefly discussed.

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Source

Proceedings of the Digital Image Computing: Techniques and Applications (DICTA 2009)

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Restricted until

2037-12-31