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Structuring a sharded image retrieval database

In previous work we described an approach to localization based in image retrieval. Specifically, we assume coarse localization based on GPS or cell tower and refine it by matching a user generated image query to a geotagged image database. We partition the image dataset into overlapping cells, each of which contains its own approximate nearest-neighbors search structure. By combining search results from multiple cells as specified by coarse localization, we have demonstrated superior retrieval accuracy on a large image database covering downtown Berkeley. In this paper, we investigate how to select the parameters of such a system e.g. size and spacing of the cells, and show how the combination of many cells outperforms a single search structure over a large region.