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Re-Ranking Process for Image Based Retrieval Using Geometric Techniques

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Author(s): Ravi Tej Kumar Maguluri | Podila Manoj | S.Roja Ramani | K.Naga Prakash | K.Ravi Kumar

Journal: International Journal of Computer Technology and Applications
ISSN 2229-6093

Volume: 02;
Issue: 06;
Start page: 4007;
Date: 2011;
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ABSTRACT
We present a fast and efficient geometric re-ranking method that can be incorporated in a feature based image-based retrieval system that utilizes a Vocabulary Tree (VT). We form feature pairs by comparing descriptor classification paths in the VT and calculate geometric similarity score of these pairs. We propose a location geometric similarity scoring method that is invariant to rotation, scale, and translation, and can be easily incorporated in mobile visual search and augmented reality systems. We compare the performance of the location geometric scoring scheme to orientation and scale geometric scoring schemes. We show in our experiments that re-ranking schemes can substantially improve recognition accuracy. We can also reduce the worst case server latency up to 1 sec and still improve the recognition performance. This entails finding the location of a query image in a large dataset containing 3 × 10^4 street side images of a city. We investigate how the traditional invariant feature matching approach falls down as the size of the database grows. In particular we show that by carefully selecting the vocabulary using the most informative features, retrieval performance is significantly improved, allowing us to increase the number of database images by a factor of 10. We also introduce a generalization of the traditional vocabulary tree search algorithm which improves performance by effectively increasing the branching factor of a fixed vocabulary tree
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