Vision and Attention - Jenkin, Michael R.M. / Harris, Laurence R. (eds.)
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It has become apparent that vision is not a passive process working on the retinal image like a film to record a perfect copy as the perception. Instead, higher-level cognitive processes such as expectancies, memories and experience play a critical, almost overriding role. This book is a review and summary of the tremendous advances that have been made in recent years on the effect of attention on visual perception. The book will appeal to vision scientists as well as to people involved in using visual processes in computer animations, display design or the sensory systems of machines.…mehr

Produktbeschreibung
It has become apparent that vision is not a passive process working on the retinal image like a film to record a perfect copy as the perception. Instead, higher-level cognitive processes such as expectancies, memories and experience play a critical, almost overriding role. This book is a review and summary of the tremendous advances that have been made in recent years on the effect of attention on visual perception. The book will appeal to vision scientists as well as to people involved in using visual processes in computer animations, display design or the sensory systems of machines. Physiologists and neuroscientists interested in any aspect of sensory or motor processes will also find this a very useful and broad-ranging volume.
  • Produktdetails
  • Verlag: Springer, Berlin
  • Artikelnr. des Verlages: 10770128
  • 2001
  • Seitenzahl: 370
  • Erscheinungstermin: 1. Juni 2001
  • Englisch
  • Abmessung: 244mm x 159mm x 22mm
  • Gewicht: 634g
  • ISBN-13: 9780387950587
  • ISBN-10: 0387950583
  • Artikelnr.: 09616764
Autorenporträt
Michael Jenkin is a Professor of Computer Science and Engineering at York University. He has co-edited a series of eight books on human and machine vision.
Inhaltsangabe
1 Vision and Attention.- 1.1 What Is Attention?.- 1.1.1 Should "attention" be regarded as a discrete behaviour?.- 1.2 Selective Visual Attention.- 1.2.1 What is selected?.- 1.2.2 How is selection achieved? How much salience is due to the sensory input itself and how much to higher processes?.- 1.2.3 What is the connection between selection and attention?.- 1.2.4 Mechanisms of selective attention.- 1.3 Parsing Attention. Is Attention Central to the Act of Seeing or is it Merely a Servant Carrying its Master to the Right Place?.- 1.4 Directing Attention.- 1.5 Conclusions.- 2 Shifts of Attention and Saccades Are Very Similar. Are They Causally Linked?.- 2.1 Spatial Attributes of Attention.- 2.2 Coordinate Space of Focal Attention.- 2.3 Overt and Covert Orientation.- 2.4 Top-Down versus Bottom-Up Attentional Control.- 2.5 Shifting Attention.- 2.6 Coupling Between Saccadic Eye Movements and Attentional Shifts.- 2.7 Adaptive Control of Saccadic Eye Movements.- 2.8 Nature of the Error Signal.- 2.9 Are Shifts of Attention also Adaptable?.- 2.10 Might Attention Provide an Error Signal to Saccade-Gain Adaptation?.- 3 Contrast Gain, Area Summation and Temporal Tuning in Primate Visual Cortex.- 3.1 Introduction.- 3.2 Gain Control.- 3.3 Contrast-Gain Control.- 3.4 Beyond the Classical Receptive Field.- 3.5 Area Summation and Contrast.- 3.6 Temporal Tuning and Contrast.- 3.7 Temporal Tuning and Contrast in V1.- 3.8 Discussion.- 4 Global Processes in Form Vision and Their Relationship to Spatial Attention.- 4.1 Introduction to the Ventral Visual Pathway.- 4.2 Components of Intermediate Form Analysis.- 4.3 Changing Views of V4.- 4.4 Evidence for Global Orientation Pooling in Human Vision.- 4.5 Neural Model for Configurai Units.- 4.6 Configural Units and Receptive Field Size.- 4.7 Evidence Pointing to Configurai Units in V4 in the Human Brain.- 4.8 Application of V4 Model Units to Faces.- 4.9 Selective Attention.- 4.10 Summary and Overview.- 5 Visual Attention: The Active Vision Perspective.- 5.1 Introduction.- 5.2 Active Vision.- 5.3 Reading.- 5.4 Scenes and Objects.- 5.5 Search.- 5.6 Rethinking Covert Attention.- 5.7 Conclusion.- 6 Complexity, Vision, and Attention.- 6.1 What Is Computational Complexity?.- 6.1.1 Some basic definitions.- 6.1.2 Dealing with NP-completeness.- 6.1.3 Vision and NP-completeness.- 6.2 Can Perception Be Modeled Computationally?.- 6.3 Visual Search.- 6.3.1 Definition.- 6.3.2 Theory.- 6.3.3 Implications.- 6.4 Complexity Level Analysis of Vision.- 6.5 The Selective-Tuning Model of Visual Attention.- 6.6 Conclusions.- 7 Motion-Disparity Interaction and the Scaling of Stereoscopic Disparity.- 7.1 Cue Combination in Depth Perception.- 7.2 Depth Scaling.- 7.2.1 Failures of depth constancy with stereo.- 7.2.2 Distance scaling of size, shape, and depth.- 7.3 Stereomotion Interaction for Depth Scaling.- 7.3.1 Why combine stereo and motion?.- 7.3.2 Evidence with a single object.- 7.3.3 Two neighboring objects.- 7.3.4 Two objects and alternative computations.- 7.3.5 Two objects at unequal distances.- 7.4 Summary.- 8 Signal Detection and Attention in Systems Governed By Multiplicative Noise.- 8.1 Introduction.- 8.2 Signal Detection Theory for Ideal and Non-ideal Observers.- 8.2.1 Overview of ideal observer analysis.- 8.2.2 The concept of probability summation.- 8.2.3 Attentional summation in 2AFC experiments derives from the difference distribution.- 8.2.4 2AFC attentional summation with uncertainty within a fixed attention window.- 8.3 Distraction Theory.- 8.4 Effects of Multiplicative Noise.- 8.4.1 Multiplicative noise makes the psychometric function shallower.- 8.4.2 Dramatic probability summation with multiplicative noise.- 8.4.3 Suprabehavioral neural sensitivity and its implications for attentional selection.- 8.4.4 Fully multiplicative noise introduces psychometric saturation.- 9 Change Blindness: Implications for the Nature of Visual Attention.- 9.1 Visual Attention: Role in Scene Perception.- 9.1.1 Change blindness.