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作者: | Lucas Paletta 等著 |
ISBN: |
9783540244219 , 3540244212
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出版社: | 北京燕山出版社 |
出版日期: | 2005-3-1 |
定价: |
¥474.60 元
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内容提要 :
This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Attention and Performance in Computational Vision, WAPCV 2004, held in Prague, Czech Republic in May 2004.
The 16 revised full papers presented together with an invited paper were carefully selected during two rounds of reviewing and improvement. The papers are organized in topical sections on attention in object and scene recognition, architectures for sequential attention, biologically plausible models for attention, and applications of attentive vision.
目录 :
Attention in Object and Scene Recognition
Distributed Control of Attention
Inherent Limitations of Visual Search and the Role of Inner-Scene Similarity
Attentive Object Detection Using an Information Theoretic Saliency Measure
Architectures for Sequential Attention
A Model of Object-Based Attention That Guides Active Visual Search to Behaviourally Relevant Locations
Learning of Position-Invariant Object Representation Across Attention Shifts
Combining Conspicuity Maps for hROIs Prediction
Human Gaze Control in Real World Search
Biologically Plausible Models for Attention
The Computational Neuroscience of Visual Cognition: Attention, Memory and Reward
Modeling Attention: From Computational Neuroscience to Computer Vision
Towards a Biologically Plausible Active Visual Search Model
Modeling Grouping Through Interactions Between Top-Down and Bottom-Up Processes: The Grouping and Selective Attention for Identification Model (G-SAIM)
TarzaNN: A General Purpose Neural Network Simulator for Visual Attention Modeling
Applications of Attentive Vision
Visual Attention for Object Recognition in Spatial 3D Data
A Visual Attention-Based Approach for Automatic Landmark Selection and Recognition
Biologically Motivated Visual Selective Attention for Face Localization
Accumulative Computation Method for Motion Features Extraction in Active Selective Visual Attention
Fast Detection of Frequent Change in Focus of Human Attention
Author Index