Video Shots’ Matching via Various Length of Multidimensional Time Sequences

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Author(s)

Zhengbing Hu 1,* Sergii V. Mashtalir 2 Oleksii K. Tyshchenko 2 Mykhailo I. Stolbovyi 2

1. School of Educational Information Technology, Central China Normal University, Wuhan, China

2. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2017.11.02

Received: 17 Jun. 2017 / Revised: 26 Jul. 2017 / Accepted: 21 Aug. 2017 / Published: 8 Nov. 2017

Index Terms

Time Series Processing, Data Clustering, Video Streams, Visual Attention, Similarity Measures, Dynamic Time Warping

Abstract

Temporal clustering (segmentation) for video streams has revolutionized the world of multimedia. Detected shots are principle units of consecutive sets of images for semantic structuring. Evaluation of time series similarity is based on Dynamic Time Warping and provides various solutions for Content Based Video Information Retrieval. Time series clustering in terms of the iterative Dynamic Time Warping and time series reduction are discussed in the paper.

Cite This Paper

Zhengbing Hu, Sergii V. Mashtalir, Oleksii K. Tyshchenko, Mykhailo I. Stolbovyi, "Video Shots’ Matching via Various Length of Multidimensional Time Sequences", International Journal of Intelligent Systems and Applications(IJISA), Vol.9, No.11, pp.10-16, 2017. DOI:10.5815/ijisa.2017.11.02

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