唤醒视频游戏AnnotatIoN（AGAIN）数据集
The Arousal video Game AnnotatIoN (AGAIN) Dataset
摘要：
我们如何在不同的任务中以一种普遍的方式对情感进行建模？这种情感的普遍表征在多大程度上是可能的？为了解决这些问题，并使研究对一般的情感计算，本文介绍了唤醒视频游戏AnnotatIoN（AGAIN）数据集。AGAIN是一个大规模的情感语料库，其中包含来自9个不同游戏的1,100多个游戏内视频（以及相应的游戏数据），这些视频以第一人称连续方式注释了124名参与者的唤醒。尽管AGAIN是为了研究情感计算在不同任务中的普遍性而创建的，但情感建模可以在其9个特定的交互式游戏中进行研究。据我们所知，AGAIN是最大的-超过37小时的注释视频和游戏日志-和最多样化的公开可用的情感数据集，基于游戏作为交互式情感激发器。
英文摘要：
How can we model affect in a general fashion, across dissimilar tasks, and to which degree are such general representations of affect even possible? To address such questions and enable research towards general affective computing, this paper introduces The Arousal video Game AnnotatIoN (AGAIN) dataset. AGAIN is a large-scale affective corpus that features over 1,100 in-game videos (with corresponding gameplay data) from nine different games, which are annotated for arousal from 124 participants in a first-person continuous fashion. Even though AGAIN is created for the purpose of investigating the generality of affective computing across dissimilar tasks, affect modelling can be studied within each of its 9 specific interactive games. To the best of our knowledge AGAIN is the largest -- over 37 hours of annotated video and game logs -- and most diverse publicly available affective dataset based on games as interactive affect elicitors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
