Multimodal computational attention for scene understanding and robotics /

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Bibliographic Details
Author / Creator:Schauerte, Boris, author.
Imprint:Switzerland : Springer, 2016.
Description:1 online resource (xxiv, 203 pages) : illustrations (some color)
Language:English
Series:Cognitive systems monographs, 1867-4925 ; volume 30
Cognitive systems monographs ; v. 30.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11255789
Hidden Bibliographic Details
ISBN:9783319337968
3319337963
3319337947
9783319337944
9783319337944
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed May 19, 2016).
Summary: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.
Other form:Print version: Schauerte, Boris. Multimodal Computational Attention for Scene Understanding and Robotics. Cham : Springer International Publishing, ©2016 9783319337944