Human-centered attention models for video summarization

Kaiming Li, Lei Guo, C. Faraco, Dajiang Zhu, Fan Deng, Tuo Zhang, Xi Jiang, Degang Zhang, Hanbo Chen, Xintao Hu, L. Miller, Tianming Liu
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引用次数: 6

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.
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视频摘要的以人为中心的注意力模型
为了方便高效的视频浏览和索引,各种视频/音频流的用户注意力模型已经被开发出来用于视频摘要和抽象。从本质上讲,人脑是多媒体内容和表示的最终用户和评估者,其响应可以为多媒体流总结提供有意义的指导。例如,能够显著激活人类大脑的视觉、听觉、语言和工作记忆系统的视频/音频片段应该被认为比其他片段更重要。值得注意的是,用户体验研究可能对这种评估有用,但就其准确捕捉大脑反应的全长动态和相互作用的能力而言,这是次优的。本文介绍了应用功能磁共振成像(fMRI)脑成像技术对多媒体流与大脑反应之间的动态和相互作用进行量化和建模的初步工作,以期建立以人为中心的注意力模型,用于指导和促进更有效和高效的多媒体总结。我们的初步结果令人鼓舞。
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