Vision Models for Target Detection and Recognition: In Memory of Arthur Menendez

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World Scientific, 1995 - Technology & Engineering - 418 pages
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This book is an international collection of contributions from academia, industry and the armed forces. It addresses current and emerging Spatial Vision Models and their application to the understanding, prediction and evaluation of the tasks of target detection and recognition. The discussion in many of the chapters is framed in terms of military targets and military vision aids. However, the techniques analyses and problems are by no means limited to this area of application. The detection and recognition of an armored vehicle from a reconnaissance image are performed by the same visual system used to detect and recognize a tumor in an X-ray. The analysis of the interaction of the human visual system with night vision devices is not different from the analysis needed in the case of an operator examining structures using a remote (endoscopic) camera, etc. The book is organized into three general sections. The first covers basic modeling of central (foveal) vision and its theoretical background. The second is centered on the evaluation of model performance in applications, while the third is dedicated to aspects of peripheral vision modeling and the expansion of peripheral modeling to include visual search.

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Quantitative Models for Pattern Detection and Discrimination
Visual Processing in the Joint SpatialSpatialFrequency
Simulating Normal and Low Vision
A Multiple Spatial Filter Model for Suprathreshold Contrast
Chapters Discrimination Information in Natural Radiance Spectra
The Oracle Approach to Target Acquisition and Search
Characterization of Task Performance with Viewing
Validation of Prediction Models for Target Acquisition
Applying Human Spatial Vision Models to RealWorld Target
A Visual Discrimination Model for Imaging System Design
Template Recognition Based on Expansion Matching
The Optical Effects
Quantifying Target Contrast in Target Acquisition Research
Chapter IS Simulation of Selective Attention and Training Effects

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