Attention in Cognitive Systems 5th International Workshop on Attention in Cognitive Systems, WAPCV 2008 Fira, Santorini, Greece, May 12, 2008 Revised Selected Papers /
This volume constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Attention in Cognitive Systems, WAPCV 2008, held in Fira, Santorini, Greece in May 2008 as an associated event of the 6th International Conference on Computer Vision Systems (ICVS 2008). Th...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2009.
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Σειρά: | Lecture Notes in Computer Science,
5395 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Attention in Scene Exploration
- On the Optimality of Spatial Attention for Object Detection
- Decoding What People See from Where They Look: Predicting Visual Stimuli from Scanpaths
- A Novel Hierarchical Framework for Object-Based Visual Attention
- Where Do We Grasp Objects? – An Experimental Verification of the Selective Attention for Action Model (SAAM)
- Contextual Cueing and Saliency
- Integrating Visual Context and Object Detection within a Probabilistic Framework
- The Time Course of Attentional Guidance in Contextual Cueing
- Conspicuity and Congruity in Change Detection
- Spatiotemporal Saliency
- Spatiotemporal Saliency: Towards a Hierarchical Representation of Visual Saliency
- Motion Saliency Maps from Spatiotemporal Filtering
- Attentional Networks
- Model Based Analysis of fMRI-Data: Applying the sSoTS Framework to the Neural Basic of Preview Search
- Modelling the Efficiencies and Interactions of Attentional Networks
- The JAMF Attention Modelling Framework
- Attentional Modeling
- Modeling Attention and Perceptual Grouping to Salient Objects
- Attention Mechanisms in the CHREST Cognitive Architecture
- Modeling the Interactions of Bottom-Up and Top-Down Guidance in Visual Attention
- Relative Influence of Bottom-Up and Top-Down Attention
- Towards Standardization of Evaluation Metrics and Methods for Visual Attention Models
- Comparing Learning Attention Control in Perceptual and Decision Space
- Automated Visual Attention Manipulation.