Attention and Performance in Computational Vision

1. Front Matter

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2. Attention in Object and Scene Recognition

   1. Distributed Control of Attention

      • Ola Ramström, Henrik I Christensen

      Pages 1-15

   2. Inherent Limitations of Visual Search and the Role of Inner-Scene Similarity

      • Tamar Avraham, Michael Lindenbaum

      Pages 16-28

   3. Attentive Object Detection Using an Information Theoretic Saliency Measure

      • Gerald Fritz, Christin Seifert, Lucas Paletta, Horst Bischof

      Pages 29-41

3. Architectures for Sequential Attention

   1. A Model of Object-Based Attention That Guides Active Visual Search to Behaviourally Relevant Locations

      • Linda Lanyon, Susan Denham

      Pages 42-56

   2. Learning of Position-Invariant Object Representation Across Attention Shifts

      • Muhua Li, James J. Clark

      Pages 57-70

   3. Combining Conspicuity Maps for hROIs Prediction

      • Claudio M. Privitera, Orazio Gallo, Giorgio Grimoldi, Toyomi Fujita, Lawrence W. Stark

      Pages 71-82

   4. Human Gaze Control in Real World Search

      • Daniel A. Gajewski, Aaron M. Pearson, Michael L. Mack, Francis N. Bartlett III, John M. Henderson

      Pages 83-99

4. Biologically Plausible Models for Attention

   1. The Computational Neuroscience of Visual Cognition: Attention, Memory and Reward

      • Gustavo Deco

      Pages 100-117

   2. Modeling Attention: From Computational Neuroscience to Computer Vision

      • Fred H. Hamker

      Pages 118-132

   3. Towards a Biologically Plausible Active Visual Search Model

      • Andrei Zaharescu, Albert L. Rothenstein, John K. Tsotsos

      Pages 133-147

   4. Modeling Grouping Through Interactions Between Top-Down and Bottom-Up Processes: The Grouping and Selective Attention for Identification Model (G-SAIM)

      • Dietmar Heinke, Yaoru Sun, Glyn W. Humphreys

      Pages 148-158

   5. TarzaNN : A General Purpose Neural Network Simulator for Visual Attention Modeling

      • Albert L. Rothenstein, Andrei Zaharescu, John K. Tsotsos

      Pages 159-167

5. Applications of Attentive Vision

   1. Visual Attention for Object Recognition in Spatial 3D Data

      • Simone Frintrop, Andreas Nüchter, Hartmut Surmann

      Pages 168-182

   2. A Visual Attention-Based Approach for Automatic Landmark Selection and Recognition

      • Nabil Ouerhani, Heinz Hügli, Gabriel Gruener, Alain Codourey

      Pages 183-195

   3. Biologically Motivated Visual Selective Attention for Face Localization

      • Sang-Woo Ban, Minho Lee

      Pages 196-205

   4. Accumulative Computation Method for Motion Features Extraction in Active Selective Visual Attention

      • Antonio Fernández-Caballero, María T. López, Miguel A. Fernández, José Mira, Ana E. Delgado, José M. López-Valles

      Pages 206-215

   5. Fast Detection of Frequent Change in Focus of Human Attention

      • Nan Hu, Weimin Huang, Surendra Ranganath

      Pages 216-230

6. Back Matter

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Inrecentresearchoncomputervisionsystems,attentionhasbeenplayingacrucialrolein mediatingbottom-upandtop-downpathsofinformationprocessing. Inappliedresearch, the development of enabling technologies such as miniaturized mobile sensors, video surveillance systems, and ambient intelligence systems involves the real-time analysis of enormous quantities of data. Knowledge has to be applied about what needs to be attendedto,andwhen,andwhattodoinameaningfulsequence,incorrespondencewith visual feedback. Methods on attention and control are mandatory to render computer vision systems more robust. The 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV 2004) was held in the Czech Technical University of Prague, Czech Republic, as an associated workshop of the 8th European Conference on Computer - sion (ECCV 2004). The goal of this workshop was to provide an interdisciplinary forum tocommunicatecomputationalmodelsofvisualattentionfromvariousviewpoints,such as from computer vision, psychology, robotics and neuroscience. The motivation for - terdisciplinarity was communication and inspiration beyond the individual community, to focus discussion on computational modelling, to outline relevant objectives for p- formance comparison, to explore promising application domains, and to discuss these with reference to all related aspects of cognitive vision. The workshop was held as a single-day, single-track event, consisting of high-quality podium and poster presen- tions. Invited talks were given by John K. Tsotsos about attention and feature binding in biologically motivated computer vision and by Gustavo Deco about the context of attention, memory and reward from the perspective of computational neuroscience. The interdisciplinary program committee wascomposed of 21 internationally r- ognized researchers.

• 3D
• Computational vision
• Computer Vision
• Performance
• ambient intelligence
• biologically motivated vision
• cognition
• cognitive science
• computer vision systems performance
• learning
• neuroscience
• object recognition
• video surveillance
• visual attention
• visual perception

• Joanneum Research, Graz, Austria

  Lucas Paletta

• Center for Vision Research (CVR) and, Department of Computer Science and Engineering, York University, Toronto, Canada

  John K. Tsotsos

• Fraunhofer IAIS, Sankt Augustin, Germany

  Erich Rome

• Behavioural Brain Sciences Centre, School of Psychology, University of Birmingham, Edgbaston, UK

  Glyn Humphreys

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