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Metric video retrieval speedup by irrelevant data elimination
Author(s): Dmytro Kinoshenko; Oleg Kobylin; Sergii Mashtalir; Mykhailo Stolbovyi
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Paper Abstract

Under content-based video search in arbitrary metric space, there arises necessity to deal with the problems concerning various aspects of Big Data specificities. Since most of the available data do not match with a query (usually in the form ‘ad exemplum’), it comes into being a construction of elimination regions of such data, which allows to significantly reduce the number of necessary comparisons for metric search. It is proposed the use of solely pivot points to calculate the distances to the query. Such approach gives possibility to exclude the entire clusters from consideration without computationally capacious operations. General case of elimination regions scheme is considered.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410O (15 March 2019); doi: 10.1117/12.2522812
Show Author Affiliations
Dmytro Kinoshenko, Kharkiv National Univ. of Radio Electronics (Ukraine)
Oleg Kobylin, Kharkiv National Univ. of Radio Electronics (Ukraine)
Sergii Mashtalir, Kharkiv National Univ. of Radio Electronics (Ukraine)
Mykhailo Stolbovyi, Kharkiv National Univ. of Radio Electronics (Ukraine)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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