Parallel Algorithms for Multidimensional Data Streams Processing with Tensor Subspace Models

被引：0
|
作者：
Cyganek, Boguslaw [1 ,2 ]
机构：
[1] AGH Univ Sci & Technol, Al Mickiewicza 30, PL-30059 Krakow, Poland
[2] Acad Comp Ctr Cyfronet AGH, Ul Nawojki 11, PL-30950 Krakow, Poland
来源：
PROCEEDINGS 2018 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS) | 2018年
关键词：
component; Tensor change detection; video shot detection; orthogonal tensor space; parallel data processing; SHOT BOUNDARY DETECTION; VIDEO;
D O I：
10.1109/HPCS.2018.00139
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper the parallel models for processing of the multi-dimensional data streams are discussed. Stream analysis is performed by tensor models and a fitness measure. The method was tested on the problem of video shot detection showing good accuracy. In this paper efficient algorithms for tensor model construction and model update in the parallel processing framework are presented. Also the parallel version for the off-line stream processing is proposed.
引用
收藏
页码：865 / 868
页数：4
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