RoleNet: Movie analysis from the perspective of social networks

Chung Yi Weng, Wei Ta Chu, Ja Ling Wu

Research output: Contribution to journalArticle

106 Citations (Scopus)

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.

Original languageEnglish
Article number4757440
Pages (from-to)256-271
Number of pages16
JournalIEEE Transactions on Multimedia
Volume11
Issue number2
DOIs
Publication statusPublished - 2009 Feb 1

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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