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Description
  • This paper is focused on classification of video footages or continuous TV broadcasts by its content. The considered classification categories (topics) are either general (talk show, sport, movie, cartoon...) or more specific (summer and winter Olympic sports, e.g. cycling, tennis, archery, box...). At first, each frame of the video is classified separately. It is shown that the classification results are more accurate and robust when the per-frame results are filtered in time domain. The main part of the paper deals with selection of robust image features and classifiers. It is shown that simple feature extractors are surpassed by complex features based on convolutional neural networks.
  • This paper is focused on classification of video footages or continuous TV broadcasts by its content. The considered classification categories (topics) are either general (talk show, sport, movie, cartoon...) or more specific (summer and winter Olympic sports, e.g. cycling, tennis, archery, box...). At first, each frame of the video is classified separately. It is shown that the classification results are more accurate and robust when the per-frame results are filtered in time domain. The main part of the paper deals with selection of robust image features and classifiers. It is shown that simple feature extractors are surpassed by complex features based on convolutional neural networks. (en)
Title
  • SPORTS VIDEO CLASSIFICATION IN CONTINUOUS TV BROADCASTS
  • SPORTS VIDEO CLASSIFICATION IN CONTINUOUS TV BROADCASTS (en)
skos:prefLabel
  • SPORTS VIDEO CLASSIFICATION IN CONTINUOUS TV BROADCASTS
  • SPORTS VIDEO CLASSIFICATION IN CONTINUOUS TV BROADCASTS (en)
skos:notation
  • RIV/49777513:23520/14:43923360!RIV15-GA0-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0090), P(GBP103/12/G084)
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
  • 46823
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/14:43923360
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Sports Classification, Topic Classification, Computer Vision, Convolutional Neural Networks, Multimedia Processing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [70E8675B5782]
http://linked.open...v/mistoKonaniAkce
  • HangZhou, CHINA
http://linked.open...i/riv/mistoVydani
  • Beijing
http://linked.open...i/riv/nazevZdroje
  • Proceedings,12th International Conference on 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
  • Campr, Pavel
  • Psutka, Josef
  • Vaněk, Jan
  • Herbig, Milan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 2164-5221
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4799-2188-1
http://localhost/t...ganizacniJednotka
  • 23520
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