Multimodal Computational Attention for Scene Understanding and Robotics

Nonfiction, Science & Nature, Technology, Robotics, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Multimodal Computational Attention for Scene Understanding and Robotics by Boris Schauerte, Springer International Publishing
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Author: Boris Schauerte ISBN: 9783319337968
Publisher: Springer International Publishing Publication: May 11, 2016
Imprint: Springer Language: English
Author: Boris Schauerte
ISBN: 9783319337968
Publisher: Springer International Publishing
Publication: May 11, 2016
Imprint: Springer
Language: English

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated. 

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This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated. 

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