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

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Springer Science & Business Media, Jan 11, 2008 - Computers - 496 pages
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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.
 

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Contents

The Embodied Dynamics of Emotion Appraisal and Attention
1
The Role of Attention in Creating a Cognitive System
21
The Influence of the Body and Action on Spatial Attention
42
Abstraction Level Regulation of Cognitive Processing Through EmotionBased Attention Mechanisms
59
Embodied Active Vision in Language Learning and Grounding
75
Language Label Learning for Visual Concepts Discovered from Video Sequences
91
Learning to Attend From BottomUp to TopDown
106
An Attentional System Combining TopDown and BottomUp Influences
123
Generating Sequence of Eye Fixations Using DecisionTheoretic Attention Model
277
Reinforcement Learning for Decision Making in Sequential Visual Attention
293
Biologically Inspired Framework for Learning and Abstract Representation of Attention Control
307
Modeling the Dynamics of Feature Binding During ObjectSelective Attention
325
Simulating Dual Task Experiments and the Temporal Dynamics of Preview Search
338
On the Role of Dopamine in Cognitive Vision
352
Differences and Interactions Between Cerebral Hemispheres When Processing Ambiguous Words
367
Some Psychophysical Insights
381

Simulating Visual Search in Natural Colour Images
141
A Bayesian Approach to Attention Control and Concept Abstraction
155
An Information Theoretic Model of Saliency and Visual Search
171
Stability Complexity and Discrimination
184
A Protoobject Based Visual Attention Model
198
Context Driven Focus of Attention for Object Detection
216
Color Saliency and Inhibition Using Static and Dynamic Scenes in Region Based Visual Attention
234
Eye Movements in RealWorld Scenes Are Affected by Perceived Direction of Gaze
251
Selective Attention in the Learning of Viewpoint and Position Invariance
263
An Alternative to Attentional Selection of Auditory Streams?
399
Simultaneous Robot Localization and Mapping Based on a Visual Attention System
417
Autonomous Attentive Exploration in Search and Rescue Scenarios
431
AttentionBased Landmark Selection in Autonomous Robotics
447
Simulation and Formal Analysis of Visual Attention in Cognitive Systems
463
RegionOriented Visual Attention Framework for Activity Detection
481
Author Index
497
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