1.

Record Nr.

UNINA9910376028903321

Autore

Angelides Marios

Titolo

MUM 2010 : proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia, December 1-3, 2010, Limassol, Cyprus

Pubbl/distr/stampa

[Place of publication not identified], : ACM, 2010

Descrizione fisica

1 online resource (239 pages)

Collana

ACM Other conferences

Soggetti

Electrical & Computer Engineering

Engineering & Applied Sciences

Telecommunications

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph



2.

Record Nr.

UNINA9910254221003321

Autore

Schauerte Boris

Titolo

Multimodal Computational Attention for Scene Understanding and Robotics / / by Boris Schauerte

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

ISBN

3-319-33796-3

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (XXIV, 203 p. 55 illus., 51 illus. in color.)

Collana

Cognitive Systems Monographs, , 1867-4925 ; ; 30

Disciplina

629.892637

Soggetti

Computational intelligence

Robotics

Automation

Artificial intelligence

Optical data processing

Pattern perception

Computational Intelligence

Robotics and Automation

Artificial Intelligence

Image Processing and Computer Vision

Pattern Recognition

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.

Sommario/riassunto

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. .