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EmotionMap: Visual Analysis of Video Emotional Content on a Map
Journal of Computer Science and Technology ( IF 1.9 ) Pub Date : 2020-05-01 , DOI: 10.1007/s11390-020-0271-2
Cui-Xia Ma , Jian-Cheng Song , Qian Zhu , Kevin Maher , Ze-Yuan Huang , Hong-An Wang

Emotion plays a crucial role in gratifying users’ needs during their experience of movies and TV series, and may be underutilized as a framework for exploring video content and analysis. In this paper, we present EmotionMap, a novel way of presenting emotion for daily users in 2D geography, fusing spatio-temporal information with emotional data. The interface is composed of novel visualization elements interconnected to facilitate video content exploration, understanding, and searching. EmotionMap allows understanding of the overall emotion at a glance while also giving a rapid understanding of the details. Firstly, we develop EmotionDisc which is an effective tool for collecting audiences’ emotion based on emotion representation models. We collect audience and character emotional data, and then integrate the metaphor of a map to visualize video content and emotion in a hierarchical structure. EmotionMap combines sketch interaction, providing a natural approach for users’ active exploration. The novelty and the effectiveness of EmotionMap have been demonstrated by the user study and experts’ feedback.

中文翻译:

EmotionMap:地图上视频情感内容的视觉分析

在用户体验电影和电视剧的过程中,情感在满足用户需求方面起着至关重要的作用,但作为探索视频内容和分析的框架可能未被充分利用。在本文中,我们提出了 EmotionMap,这是一种在 2D 地理中为日常用户呈现情感的新方法,将时空信息与情感数据相融合。该界面由互连的新颖可视化元素组成,以促进视频内容的探索、理解和搜索。EmotionMap可以让你一目了然地了解整体情绪,同时也可以快速了解细节。首先,我们开发了EmotionDisc,它是一种基于情感表征模型收集观众情感的有效工具。我们收集观众和角色的情感数据,然后整合地图的比喻,以层次结构可视化视频内容和情感。EmotionMap结合了草图交互,为用户的主动探索提供了一种自然的方式。EmotionMap 的新颖性和有效性已被用户研究和专家反馈所证明。
更新日期:2020-05-01
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