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.

Keywords:
Automatic summarization Computer science Search engine indexing Multimedia Abstraction Functional magnetic resonance imaging Human–computer interaction Visualization Variety (cybernetics) Artificial intelligence

Metrics

5
Cited By
0.96
FWCI (Field Weighted Citation Impact)
34
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Music and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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