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Similarity Search and Applications: 5th International by Santosh S. Vempala (auth.), Gonzalo Navarro, Vladimir Pestov

By Santosh S. Vempala (auth.), Gonzalo Navarro, Vladimir Pestov (eds.)

This publication constitutes the court cases of the fifth overseas convention on Similarity seek and functions, SISAP 2012, held in Toronto, Canada, in August 2012. The 14 complete papers provided during this quantity, including 2 demo papers and a couple of invited talks, have been rigorously reviewed and chosen from 19 submissions. The papers take care of a few of the such a lot correct features of similarity looking out and are prepared in topical sections named: new situations and techniques; bettering metric info constructions; dealing with scalability concerns; looking in particular areas; and new similarity spaces.

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Extra resources for Similarity Search and Applications: 5th International Conference, SISAP 2012, Toronto, ON, Canada, August 9-10, 2012. Proceedings

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Hence, the impact of the proposed framework is two-fold. , multimedia retrieval, time series databases, biometric databases, etc. Since applications come from different domains outside the computer science, the contribution of our outcomes is truly multi-disciplinary.

M. Barrios, B. Bustos, and T. Skopal either updated with an ∞ distance; 2) the cell is left unmodified but before any read the query stored in the cell is matched with the last query for that column (the experimental section uses the latter). With this strategy, each row is sparse, containing at most p distances between d(qi−p , oj ) and d(qi , oj ). 2. The distance d(qi , oj ) is compared to every distance in j th row and the highest distance in the row is replaced. With this strategy, each row stores p unsorted distances between d(q1 , oj ) and d(qi , oj ).

Each slice calculates a histogram of 16 bins for R, G, and B channels, and each bin with 8-bits linear quantization, producing a vector of 192 bytes. The Keyframe (KF), reduces the frame to 11×9 pixels and uses the value for each pixel, producing a vector of 99 bytes. These descriptors are calculated for all the frames in a segment and then averaged. R is the set of reference segments (|R|=211,479 segments), and Q is the set of query segments (|Q|=2,692 segments). The correct answer for a segment q ∈ Q is the reference segment rq ∈ R for which q is a copy.

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