Metric video retrieval speedup by irrelevant data elimination

Dmytro Kinoshenko; Oleg Kobylin; Sergii Mashtalir; Mykhailo Stolbovyi

doi:10.1117/12.2522812

15 March 2019 Metric video retrieval speedup by irrelevant data elimination

Dmytro Kinoshenko, Oleg Kobylin, Sergii Mashtalir, Mykhailo Stolbovyi

Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018); 110410O (2019) https://doi.org/10.1117/12.2522812
Event: Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany

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.

Citation Download Citation

Dmytro Kinoshenko, Oleg Kobylin, Sergii Mashtalir, and Mykhailo Stolbovyi "Metric video retrieval speedup by irrelevant data elimination", Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410O (15 March 2019); https://doi.org/10.1117/12.2522812

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