Human-centered attention models for video summarization

Kaiming Li, Tuo Zhang, Xintao Hu, Dajiang Zhu, Hanbo Chen, Xi Jiang, Fan Deng, Lei Guo, Carlos Faraco, Degang Zhang, Junwei Han, Xian Sheng Hua, Tianming Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

A variety of user attention models for video/audio streams have been developed for video summarization and abstraction, in order to facilitate efficient video browsing and indexing. Essentially, human brain is the end user and evaluator of multimedia content and representation, and its responses can provide meaningful guidelines for multimedia stream summarization. For example, video/audio segments that significantly activate the visual, auditory, language and working memory systems of the human brain should be considered more important than others. It should be noted that user experience studies could be useful for such evaluations, but are suboptimal in terms of their capability of accurately capturing the full-length dynamics and interactions of the brain's response. This paper presents our preliminary efforts in applying the brain imaging technique of functional magnetic resonance imaging (fMRI) to quantify and model the dynamics and interactions between multimedia streams and brain response, when the human subjects are presented with the multimedia clips, in order to develop human-centered attention models that can be used to guide and facilitate more effective and efficient multimedia summarization. Our initial results are encouraging.

Original languageEnglish
Title of host publicationInternational Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, ICMI-MLMI 2010
DOIs
StatePublished - 2010
Event1st International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, ICMI-MLMI 2010 - Beijing, China
Duration: 8 Nov 201010 Nov 2010

Publication series

NameInternational Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, ICMI-MLMI 2010

Conference

Conference1st International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, ICMI-MLMI 2010
Country/TerritoryChina
CityBeijing
Period8/11/1010/11/10

Keywords

  • abstraction
  • attention models
  • brain imaging
  • summarization

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