Cargando…

Multimodal computational attention for scene understanding and robotics

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...

Descripción completa

Detalles Bibliográficos
Autor principal: Schauerte, Boris
Lenguaje:eng
Publicado: Springer 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-33796-8
http://cds.cern.ch/record/2157650
_version_ 1780950727155253248
author Schauerte, Boris
author_facet Schauerte, Boris
author_sort Schauerte, Boris
collection CERN
description 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. .
id cern-2157650
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2016
publisher Springer
record_format invenio
spelling cern-21576502021-04-21T19:40:57Zdoi:10.1007/978-3-319-33796-8http://cds.cern.ch/record/2157650engSchauerte, BorisMultimodal computational attention for scene understanding and roboticsEngineeringThis 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. .Springeroai:cds.cern.ch:21576502016
spellingShingle Engineering
Schauerte, Boris
Multimodal computational attention for scene understanding and robotics
title Multimodal computational attention for scene understanding and robotics
title_full Multimodal computational attention for scene understanding and robotics
title_fullStr Multimodal computational attention for scene understanding and robotics
title_full_unstemmed Multimodal computational attention for scene understanding and robotics
title_short Multimodal computational attention for scene understanding and robotics
title_sort multimodal computational attention for scene understanding and robotics
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-33796-8
http://cds.cern.ch/record/2157650
work_keys_str_mv AT schauerteboris multimodalcomputationalattentionforsceneunderstandingandrobotics