Rasche The Making of a Neuromorphic Visual System

2005
ISBN: 978-0-387-23469-4
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 140 Seiten, eBook

This book presents an approach to the construction of a visual system, which is behaviorally, computationally and neurally motivated. The goal is to characterize the process of visual categorization and to find a suitable representation format that can successfully deal with the structural variability existent within visual categories. The book reviews past and existent theories of visual object and shape recognition in the fields of computer vision, neuroscience and psychology. The entire range of computations is discussed, as are region-based approaches and are modeled with wave-propagating networks. A completely novel shape recognition architecture is proposed that can recognize simple shapes under various degraded conditions. It is discussed how such networks can be used for constructing basic-level object representations. It is envisioned how those networks can be implemented using the method of neuromorphic engineering.

Zielgruppe

Research

Autoren/Hrsg.

Rasche, Christoph

Inhaltsverzeichnis

1: Seeing: Blazing Processing Characteristics
1.1 An Infinite Reservoir of Information
1.2 Speed

1.3 Illusions
1.4 Recognition Evolvement
1.5 Basic-Level Categorization
1.6 Memory Capacity and Access
1.7 Summary

2: Category Representation and Recognition Evolvement
2.1 Structural Variability Independence
2.2 Viewpoint Independence
2.3 Representation and Evolvement
2.4 Recapitulation
2.5 Refining the Primary Engineering Goal

3: Neuroscientific Inspiration
3.1 Hierarchy and Models
3.2 Criticism and Variants
3.3 Speed
3.4 Alternative ‘Codes’
3.5 Alternative Shape Recognition
3.6 Insight from Cases of Visual Agnosia
3 7 Neuronal Level
3.8 Recapitulation and Conclusion

4: Neuromorphic Tools
4.1 The Transistor
4.2 A Synaptic Circuit
4.3 Dendritic Compartments
4.4 An Integrate-and-Fire Neuron
4.5 A Silicon Cortex
4.6 Fabrication Vagrancies require Simplest Models
4.7 Recapitulation

5: Insight From Line Drawings Studies
5.1 A Representation with Polygons

5.2 A Representation with Polygons and their Context
5.3 Recapitulation

6: Retina Circuits Signaling and Propagating Contours

6.1 The Input: a Luminance Landscape

6.2 Spatial Analysis in the Real Retina

6.3 The Propagation Map

6.4 Signaling Contours in Gray-Scale Images

6.5 Recapitulation

7: The Symmetric-Axis Transform

7.1 The Transform

7.2 Architecture

7.3 Performance

7.4 SAT Variants

7.5 Fast Waves

7.6 Recapitulation

8: Motion Detection
8.1 Models
8.2 Speed Detecting Architectures
8.3 Simulation
8.4 Biophysical Plausibility
8.5 Recapitulation

9: Neuromorphic Architectures: Pieces and Proposals

9.1 Integration Perspectives

9.2 Position and Size Invariance

9.3 Architecture for a Template Approach

9.4 Basic-Level Representations

9.5 Recapitulation

10: Shape Recognition with ContourPropagation Fields

10.1 The Idea of the Contour Propagation Field

10.2 Architecture

10.3 Testing

10.4 Discussion

10.5 Learning

10.6 Recapitulation

11: Scene Recognition
11.1 Objects in Scenes, Scene Regularity
11.2 Representation, Evolvement, Gist
11.3 Scene Exploration
11.4 Engineering
11.5 Recapitulation

12: Summary
12.1 The Quest for Efficient Representation and Evolvement
12.2 Contour Extraction and Grouping
12.3 Neuroscientific Inspiration
12.4 Neuromorphic Implementation
12.5 Future Approach

Terminology

References

Index
Keywords
Abbreviations