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Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint

4th International Workshop on Attention in Cognitive Systems, WAPCV 2007 Hyderabad, India, January 8, 2007 Revised Selected Papers

  • Lucas Paletta
  • Erich Rome
Conference proceedings WAPCV 2007

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4840)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4840)

Table of contents

  1. Front Matter
  2. Embodiment of Attention

    1. Robert Lowe, Carlos Herrera, Anthony Morse, Tom Ziemke
      Pages 1-20
    2. Catherine L. Reed, John P. Garza, Ralph J. Roberts Jr.
      Pages 42-58
    3. Prithwijit Guha, Amitabha Mukerjee
      Pages 91-105
  3. Cognitive Control of Attention

    1. Hector Jasso, Jochen Triesch
      Pages 106-122
    2. Babak Rasolzadeh, Alireza Tavakoli Targhi, Jan-Olof Eklundh
      Pages 123-140
    3. Dietmar Heinke, Andreas Backhaus, Yarou Sun, Glyn W. Humphreys
      Pages 141-154
    4. Saied Haidarian Shahri, Majid Nili Ahmadabadi
      Pages 155-170
  4. Modeling of Saliency and Visual Search

    1. Neil D. B. Bruce, John K. Tsotsos
      Pages 171-183
    2. Francesco Orabona, Giorgio Metta, Giulio Sandini
      Pages 198-215
    3. Roland Perko, Aleš Leonardis
      Pages 216-233
    4. Monica S. Castelhano, Mareike Wieth, John M. Henderson
      Pages 251-262
  5. Sequential Attention

  6. Biological Aspects of Attention

    1. Albert L. Rothenstein, John K. Tsotsos
      Pages 325-337
    2. Julien Vitay, Fred H. Hamker
      Pages 352-366
    3. Orna Peleg, Zohar Eviatar, Hananel Hazan, Larry Manevitz
      Pages 367-380
    4. Kuntal Ghosh, Sankar K. Pal
      Pages 381-398
  7. Applications of Attentive Vision

    1. Simone Frintrop, Patric Jensfelt, Henrik Christensen
      Pages 417-430
    2. Andrea Carbone, Daniele Ciacelli, Alberto Finzi, Fiora Pirri
      Pages 431-446
    3. Antonio Chella, Irene Macaluso, Lorenzo Riano
      Pages 447-462
    4. Tibor Bosse, Peter-Paul van Maanen, Jan Treur
      Pages 463-480
    5. Thomas Geerinck, Hichem Sahli
      Pages 481-496
    6. Andrea Carbone, Daniele Ciacelli, Alberto Finzi, Fiora Pirri
      Pages E1-E1
  8. Back Matter

About these proceedings

Introduction

Attentionhasbeenrepresentingacorescienti?ctopicinthedesignofAI-enabled systems within the last decades. Today, in the ongoing debate, design, and c- putationalmodelingofarti?cialcognitivesystems,attentionhasgainedacentral position as a focus of research. For instance, attentional methods are considered in investigating the interfacing of sensory and cognitive information processing, for the organization of behaviors, and for the understanding of individual and social cognition in re?ection of infant development. Whilevisualcognitionplaysacentralroleinhumanperception,?ndingsfrom neuroscience and experimental psychology have provided strong evidence about theperception-actionnatureofcognition.Theembodiednatureofsensory-motor intelligence requires a continuous and focused interplay between the control of motor activities and the interpretation of feedback from perceptual modalities. Decision making about the selection of information from the incoming sensory stream – in tune with contextual processing on a current task and an agent’s global objectives – becomes a further challenging issue in attentional control. Attention must operate at interfaces between bottom-up driven world int- pretation and top-down driven information selection, thus acting at the core of arti?cial cognitive systems. These insights have already induced changes in AI-related disciplines, such as the design of behavior-based robot control and the computational modeling of animats. Today, the development of enabling technologiessuch as autonomous robotic systems,miniaturizedmobile–evenwearable–sensors,andambientintelligence systems involves the real-time analysis of enormous quantities of data. These data have to be processed in an intelligent way to provide “on time delivery” of the required relevant information. Knowledge has to be applied about what needs to be attended to, and when, and what to do in a meaningful sequence, in correspondence with visual feedback.

Keywords

Simulation active perception artificial intelligence autonomous robotics cognitive science computational vision computer vision concept learning context awareness entropy gist perception information theo learning robot robotics

Editors and affiliations

  • Lucas Paletta
    • 1
  • Erich Rome
    • 2
  1. 1.Joanneum Research, Forschungsgesellschaft mbH, Computational Perception Group,Institute of Digital Image ProcessingGrazAustria
  2. 2.Autonomous Intelligent Systems (AIS), Autonomous Robots DepartmentFraunhofer InstituteSankt AugustinGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-77343-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-77342-9
  • Online ISBN 978-3-540-77343-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site