摘要
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 In Social Net,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,In Social Net 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 In Social Net 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.
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 In Social Net, 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, In Social Net 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 In Social Net 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.
基金
supported by National Natural Science Foundation of China(No.61802278).
