Object Recognition in Man, Monkey, and Machine

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Format: Paperback
Pub. Date: 1999-03-15
Publisher(s): Bradford Books
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Summary

These interconnected essays on three-dimensional visual object recognition present cutting-edge research by some of the most creative neuroscientific, cognitive, and computational scientists in the field. Cassandra Moore and Patrick Cavanagh take a classic demonstration, the perception of "two-tone" images, and turn it into a method for understanding the nature of object representations in terms of surfaces and the interaction between bottom-up and top-down processes. Michael J. Tarr and Isabel Gauthier use computer graphics to study whether viewpoint-dependent recognition mechanisms can generalize between exemplars of perceptually defined classes. Melvyn A. Goodale and G. Keith Humphrey use innovative psychophysical techniques to investigate dissociable aspects of visual and spatial processing in brain-injured subjects. D. I. Perrett, M. W. Oram, and E. Ashbridge combine neurophysiological single-cell data from monkeys with computational analyses for a new way of thinking about the mechanisms that mediate viewpoint-dependent object recognition and mental rotation. Shimon Ullman also addresses possible mechanisms to account for viewpoint-dependent behavior, but from the perspective of machine vision. Finally, Philippe G. Schyns synthesizes work from many areas, to provide a coherent account of how stimulus class and recognition task interact. The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition.

Author Biography

Heinrich Bülthoff is Professor and Director of the Perception, Cognition, and Action Department at the Max Planck Institute for Biological Cybernetics in Tübingen.

Table of Contents

Image-based object recognition in man, monkey and machine
Abstract
Introduction
Models of recognition
Evidence for the image-based approach
Reconciling image-based and structural-description models
Current problems with image-based models
Class generalization and categorical representation
Hyper-sensitivity, inflexibility and combinatorial explosions
Matching algorithms and normalization mechanisms
Extending the image-based approach
Interpolation across views
Interpolation across exemplars
Temporal associations
Explicit structural information
Implicit structural information
Perceptual expertise
Conclusion
Acknowledgements
References
Three-dimensional object recognition based on the combination of views
Abstract
Recognition and the variability of object views
An empirical comparison of intra- and inter-object variability
The combination of object views
The view-combination property
Using two views only
A single view of a symmetric object
Using view-combinations for recognition
Adding abstract descriptions
Class-based view combinations
Extensions to the basic scheme
Perspective projections
Non-linear image combinations
Occlusion
Multiple models and the role of classification
Psychophysical and physiological aspects
Psychophysical evidence
New views are more difficult than trained ones
The difficulty persists when strong 3D cues are available
Generalization improves with additional views
Better generalization to same-axis rotation
Recognition is better than an 'ideal 2D observer'
Physiological aspects
Cells in IT are usually view-selective
The response is determined by 2D similarity of views
Lesion evidence for the primacy of stored views
Conclusions
Acknowledgements
References
Recovery of 3D volume from 2-tone images of novel objects
Abstract
Introduction
Characterization of the image and the problem
Experiment 1: single-Part objects
Stimuli
Methods
Results and discussion
Experiment 2: multiple-Part objects
Stimuli and methods
Results and discussion
General discussion
Object complexity - a demonstration
Experiment 3: adequate object contour
Stimuli
Methods
Results
Discussion
Illumination hypotheses
Illumination information from recognizable objects
Illumination information from multiple views
Explicit illumination information
Illumination information from scenes
Conclusions
References
Do viewpoint-dependent mechanisms generalize across members of a class?
Abstract
Introduction
Evidence for generalization
Image-based class generalization
Experiment 1
Method
Subjects
Materials
Design and procedure
Results and discussion
Experiment 2
Method
Subjects
Materials
Design and procedure
Results and discussion
Experiment 3
Method
Subjects
Materials
Design and procedure
Results and discussion
General discussion
An image-based network for class recognition
Neural correlates
Conclusions
Acknowledgements
References
Evidence accumulation in cell populations responsive to faces: an account of generalisation of rec...
Abstract
Introduction
Problems with the mental rotation account
A physiological explanation
View
Object symmetry
Orientation
Behavioural effects of orientation
Size
Recognition from the whole or Part of an object
Discussion
Recognition of unusual views following brain damage
The limits of generalisation
Measures of recognition: detection, discrimination, and categorisation
Population vector hypothesis
Evidence for mental transformations
Explaining behavioural generalisation from physiological mechanisms
Acknowledgements
References
Diagnostic recognition: task constraints, object information, and their interactions
Abstract
Introduction
The diagnostic recognition framework: interactions of task constraints and object information
Example 1: diagnostic recognition and viewpoint-dependence
Example 2: object information and categorization
Everyday object recognition
The task demands of 'everyday object recognition'
Difficulties with Part information for all basic-level tasks
A basic level without Parts
A relative basic-level
Towards a formal model of task constraints
Lessons from task constraints
Perceptual information in object everyday recognition
Interactions of spatial scales and diagnostic cues in scene recognition
General discussion
Implications of diagnostic recognition for studies of object recognition, categorization and pe...
Limitations of diagnostic recognition for studies of object representations
Concluding remarks
Acknowledgements
References
The objects of action and perception
Abstract
Introduction
What is vision?
Vision for acting on the world
Vision for perceiving the world
Action and perception systems in the primate brain: dorsal and ventral streams
Neuropsychological studies of the dorsal stream
Neuropsychological studies of the ventral stream
Electrophysiological and behavioural studies in the monkey
Neuro-imaging studies in humans
Differences in the visual transformations mediating action and perception
Dissociations between action and perception in normal subjects
The action/perception distinction in computational vision
Getting it together: interactions between action and perception
Acknowledgements
References
Index
Table of Contents provided by Publisher. All Rights Reserved.

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