About: Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures     Goto   Sponge   NotDistinct   Permalink

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Description
  • Video scene segmentation is a process for dividing video into semantically meaningful blocks. This can help e.g. search engines to divide video into better manageable parts and enable more relevant search in video. Unfortunately, scene segmentation is based on the semantic and therefore it is a difficult task for computers. This work is preliminary study involved into supervised video scene segmentation, which is driven by the way how human segments scenes in a movie. Since these video segments represent semantic parts in video, it can be used for better video annotation and also for searching in videos. As a training set, only high quality movies were used and from these movies 100 training samples have been extracted and used for evaluation. Resulting model is a method based on general color layout, Tamura similarity measure and k-nearest neighbors achieving 97.00% accuracy.
  • Video scene segmentation is a process for dividing video into semantically meaningful blocks. This can help e.g. search engines to divide video into better manageable parts and enable more relevant search in video. Unfortunately, scene segmentation is based on the semantic and therefore it is a difficult task for computers. This work is preliminary study involved into supervised video scene segmentation, which is driven by the way how human segments scenes in a movie. Since these video segments represent semantic parts in video, it can be used for better video annotation and also for searching in videos. As a training set, only high quality movies were used and from these movies 100 training samples have been extracted and used for evaluation. Resulting model is a method based on general color layout, Tamura similarity measure and k-nearest neighbors achieving 97.00% accuracy. (en)
Title
  • Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures
  • Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures (en)
skos:prefLabel
  • Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures
  • Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures (en)
skos:notation
  • RIV/00216305:26220/13:PU104500!RIV14-MPO-26220___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(FR-TI4/151), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 109023
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/13:PU104500
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • image analysis, machine learning, similarity measure, video segmentation. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [251F39667BAD]
http://linked.open...v/mistoKonaniAkce
  • Rome
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • 36th International Conference on Telecommunications and Signal processing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Burget, Radim
  • Mašek, Jan
  • Uher, Václav
  • Dutta, Malay Kishore
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-1-4799-0402-0
http://localhost/t...ganizacniJednotka
  • 26220
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