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Human-centered attention models for video summarization
Li K., Guo L., Faraco C., Zhu D., Deng F., Zhang T., Jiang X., Zhang D., Chen H., Hu X., Miller S., Liu T.  ICMI-MLMI 2010 (International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, Beijing, China, Nov 8-10, 2010)1-8.2010.Type:Proceedings
Date Reviewed: Mar 8 2011

Analyzing brain responses to multimedia input is an extremely interesting area of research, encompassing both user experience and user attention models.

Functional magnetic resonance imaging (fMRI) is one technique that the authors use to study the interactions between multimedia input streams and the brain. Using this method, one can classify and draw connections between various brain regions and their interactions, with regard to visual and auditory perception, language, memory, and so on. Low- and high-level features are used to build a human-centered attention model. Following natural stimuli, the authors map various regions of interest and model them using a simple computational model. The human-centered attention model uses video abstraction techniques.

According to the authors, their work “suggests that [the] fMRI brain imaging technique can play an important role in linking the two research areas of brain science and multimedia computing, facilitating better multimedia understanding and management.”

Reviewer:  George Popescu Review #: CR138877 (1110-1072)
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Human Information Processing (H.1.2 ... )
 
 
Video (H.5.1 ... )
 
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