An annotated video dataset for computing video memorability

被引:5
作者
Kiziltepe, Rukiye Savran [1 ]
Sweeney, Lorin [2 ]
Constantin, Mihai Gabriel [3 ]
Doctor, Faiyaz [1 ]
de Herrera, Alba Garcia Seco [1 ]
Demarty, Claire-Helene [4 ]
Healy, Graham [2 ]
Ionescu, Bogdan [3 ]
Smeaton, Alan F. [2 ]
机构
[1] Univ Essex, Colchester, Essex, England
[2] Dublin City Univ, Insight Ctr Data Analyt, Dublin 9, Ireland
[3] Univ Politehn Bucuresti, Bucharest, Romania
[4] InterDigital, R&I, Paris, France
来源
DATA IN BRIEF | 2021年 / 39卷
基金
爱尔兰科学基金会; 欧盟地平线“2020”;
关键词
Video memorability; Machine learning; Human memory; Mediaeval benchmark;
D O I
10.1016/j.dib.2021.107671
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:9
相关论文
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