An annotated video dataset for computing video memorability

Savran Kiziltepe R., Sweeney L., Constantin M. G., Doctor F., De Herrera A. G. S., Demarty C., ...Daha Fazla

DATA IN BRIEF, cilt.39, 2021 (ESCI) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 39
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.dib.2021.107671
  • Dergi Adı: DATA IN BRIEF
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, BIOSIS, Directory of Open Access Journals
  • Anahtar Kelimeler: Video memorability, Machine learning, Human memory, Mediaeval benchmark
  • Karadeniz Teknik Üniversitesi Adresli: Hayır

Özet

Using a collection of publicly available links to short form video clips of an average of 6 seconds duration each, 1275 users manually annotated each video multiple times to indicate both long-term and short-term memorability of the videos. The annotations were gathered as part of an online memory game and measured a participant's ability to recall having seen the video previously when shown a collection of videos. The recognition tasks were performed on videos seen within the previous few minutes for short-term memorability and within the previous 24 to 72 hours for longterm memorability. Data includes the reaction times for each recognition of each video. Associated with each video are text descriptions (captions) as well as a collection of image-level features applied to 3 frames extracted from each video (start, middle and end). Video-level features are also provided. The dataset was used in the Video Memorability task as part of the MediaEval benchmark in 2020. (C) 2021 The Author(s). Published by Elsevier Inc.