Video Shots‘ Matching via Various Length of Multidimensional Time Sequences

Video Shots‘ Matching via Various Length of Multidimensional Time Sequences

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...

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Veröffentlicht in:International journal of intelligent systems and applications 2017-11, Vol.9 (11), p.10-16
Hauptverfasser: Hu, Zhengbing, Mashtalir, Sergii V., Tyshchenko, Oleksii K., Stolbovyi, Mykhailo I.
Format: Artikel
Sprache:eng
Schlagworte:
Clustering
Image detection
Image segmentation
Information retrieval
Multimedia
Sequences
Time series
Video data
Warping
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Zusammenfassung: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.
ISSN:2074-904X
2074-9058
DOI:10.5815/ijisa.2017.11.02