RoleNet: movie analysis from the perspective of social networks

  • Authors:

  • Chung-Yi Weng;Wei-Ta Chu;Ja-Ling Wu

  • Affiliations:

  • Department of Computer Science and Information Engineering, Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan;Department of Computer Science and Information Engineering, Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan

  • Venue:
  • IEEE Transactions on Multimedia - Special issue on integration of context and content
  • Year:
  • 2009

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Abstract

With the idea of social network analysis, we propose a novel way to analyze movie videos from the perspective of social relationships rather than audiovisual features. To appropriately describe role's relationships in movies, we devise a method to quantify relations and construct role's social networks, called RoleNet. Based on RoleNet, we are able to perform semantic analysis that goes beyond conventional feature-based approaches. In this work, social relations between roles are used to be the context information of video scenes, and leading roles and the corresponding communities can be automatically determined. The results of community identification provide new alternatives in media management and browsing. Moreover, by describing video scenes with role's context, social-relation-based story segmentation method is developed to pave a new way for this widely-studied topic. Experimental results show the effectiveness of leading role determination and community identification. We also demonstrate that the social-based story segmentation approach works much better than the conventional tempo-based method. Finally, we give extensive discussions and state that the proposed ideas provide insights into context-based video analysis.