Multimodal Computational Attention for Scene Understanding and Robotics
Schauerte, Boris.
Multimodal Computational Attention for Scene Understanding and Robotics by Boris Schauerte - Cham Springer International Publishing 2016 - 1 recurso en línea (XXIV, 203 p.) 55 ilustraciones, 51 ilustraciones en color - Cognitive Systems Monographs 30 1867-4925 . - Cognitive Systems Monographs 30 .
Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.
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. .
9783319337968
Inteligencia artificial
Proceso de imágenes
Ingeniería--Congresos y asambleas
TJ211.3 / S338 2016 EB
006.3
Multimodal Computational Attention for Scene Understanding and Robotics by Boris Schauerte - Cham Springer International Publishing 2016 - 1 recurso en línea (XXIV, 203 p.) 55 ilustraciones, 51 ilustraciones en color - Cognitive Systems Monographs 30 1867-4925 . - Cognitive Systems Monographs 30 .
Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.
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. .
9783319337968
Inteligencia artificial
Proceso de imágenes
Ingeniería--Congresos y asambleas
TJ211.3 / S338 2016 EB
006.3