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In This Chapter
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Vision: Nonlinear Dynamic Approaches
- Introduction
- Basic Tools and Practices of Nonlinear Dynamics
- Options for Modeling Purely Temporal Problems
- Potential-Based Dynamics vs. Explicit Interactions between Component Mechanisms
- Spatiotemporal Modeling
- A Beastiery of Nonlinear Dynamic Phenomena and Their Perceptual/Neural Correlates
- Winner-Take-All Competition Models
- Stochastic Resonance
- Perceptual Oscillations and Multistability
- Hysteresis
- Enhanced Contrast (Antihysteresis)
- Coupled Oscillators and Synchronization
- Psychophysical Power Laws
- 1/f Spectra
- Pattern Formation
- Conclusion
- References
- Appendix A
- Appendix B
Abstract
Nonlinear dynamic approaches make it possible to tackle visual phenomena that were previously unaddressable. Visual phenomena that once seemed mysterious can now be understood as emergent properties of large-scale nonlinear collective systems. Mathematicians and physicists have devoted decades to develop sophisticated techniques that vision researchers can appropriate.
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