InSocialNet: Interactive visual analytics for role-event videos
InSocialNet: Interactive visual analytics for role-event videos
复制标题
InSocialNet：角色事件视频的交互式视觉分析
DOI：
10.1007/s41095-019-0157-9
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发表时间：
2019
影响因子：
6.9
通讯作者：
Zhang Jiawan
中科院分区：
文献类型：
--
作者：
Pan Yaohua;Niu Zhibin;Wu Jing;Zhang Jiawan
角色事件的视频丰富了信息，但在故事层面上挑战。角色的社会角色和行为模式在很大程度上取决于字符和背景事件之间的相互作用。了解它们需要长时间对视频内容的分析，这超出了目前设计用于分析短时动态的算法的能力。在本文中，我们提出了InsocialNet，这是一种交互式视频分析工具，用于分析角色事件视频的内容。它会自动，动态地构建社交网络，从可利用面部和表达识别的角色事件视频中构建社交网络，并为视频内容进行交互式分析提供了视觉界面。 InsocialNet与后端的社交网络分析一起，支持用户在输入视频中调查角色，其关系，社交角色，派别和事件。我们进行案例研究，以证明官方网络从角色事件视频中收获丰富的信息的有效性。我们认为，当前的原型实施可以扩展到电影分析之外的应用程序，例如社会心理学实验，以帮助了解人群社会行为。
Role-event videos are rich in information but challenging to be understood at the story level. The social roles and behavior patterns of characters largely depend on the interactions among characters and the background events. Understanding them requires analysis of the video contents for a long duration, which is beyond the ability of current algorithms designed for analyzing short-time dynamics. In this paper, we propose InSocialNet, an interactive video analytics tool for analyzing the contents of role-event videos. It automatically and dynamically constructs social networks from role-event videos making use of face and expression recognition, and provides a visual interface for interactive analysis of video contents. Together with social network analysis at the back end, InSocialNet supports users to investigate characters, their relationships, social roles, factions, and events in the input video. We conduct case studies to demonstrate the effectiveness of InSocialNet in assisting the harvest of rich information from role-event videos. We believe the current prototype implementation can be extended to applications beyond movie analysis, e.g., social psychology experiments to help understand crowd social behaviors.