Multi-sketch Semantic Video Browser

Kuboň, David; Blažek, Adam; Lokoč, Jakub; Skopal, Tomáš

doi:10.1007/978-3-319-27674-8_41

Cited by 6 publications

(1 citation statement)

References 12 publications

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“…In two SVM classifiers are having a sliding window, to distinguish cuts and continuous changes, individually. A few highlights from each casing, and afterward utilizes the SVM to characterize the edges utilizing these highlights into three classifications: cut, progressive change, and others [4,5].…”

Section: Algorithmmentioning

confidence: 99%

Content Based Video Retrieval Systems with Local Features: A Survey

Kalakoti

Prabhakaran

Sudhakar

2018

AJCST

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With the improvement of mixed media information composes and accessible transfer speed there is immense interest of video retrieving frameworks, as clients move from content based recovery frameworks to content based retrieval frameworks. Determination of removed features assume an imperative job in substance based video retrieving paying little mind to video qualities being under thought. This work assists the up and coming analysts in the field of video retrieving with getting the thought regarding distinctive procedures and strategies accessible for the video recovery. These highlights are proposed for choosing, ordering and positioning as indicated by their potential enthusiasm to the client. Great feature determination likewise permits the time and space expenses of the recovery procedure to be lessened. This overview surveys the fascinating highlights that can be separated from video information for ordering and retrieving alongside likeness estimation techniques. We likewise recognize present research issues in territory of content based video retrieving frameworks.

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Section: Algorithmmentioning

confidence: 99%