Related Experiment Video
Updated: Aug 6, 2026
08:04
Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
Published on: December 4, 2013
Temporal dynamics of stereo correspondence bi-stability
Ross Goutcher1, Pascal Mamassian
1School of Psychology, University of St Andrews, St Andrews, UK. rg70@st-andrews.ac.uk
Vision Research
|August 2, 2006
Summary
This study reveals two phases in how the brain solves the stereo correspondence problem with ambiguous images. Initial perception is biased, followed by a sustained, stable state influencing visual perception.
Area of Science:
- Vision Science
- Perceptual Psychology
- Computational Neuroscience
Background:
- The stereo correspondence problem is crucial for depth perception.
- Ambiguous stereoscopic stimuli can lead to bistable perception, where observers switch between solutions.
- Understanding the temporal dynamics of this perceptual switching is key to visual processing.
Purpose of the Study:
- To investigate the temporal dynamics of perceptual switching in response to periodic stereoscopic stimuli.
- To examine how inter-ocular contrast and disparity influence correspondence matching.
- To identify distinct phases in the biasing of perceptual states.
Main Methods:
- Participants viewed ambiguous stereograms with regularly spaced dots for 60 seconds.
- Auditory prompts (every ~2s) cued participants to report perceived depth (front or back).
- Inter-ocular contrast and disparity were manipulated to alter correspondence preference.
Main Results:
- An initial bias towards perceiving uncrossed disparity was observed.
- Perceptual preference and stability stabilized after an initial period of change.
- Manipulating matching preference influenced both transient and sustained percepts.
Conclusions:
- The study identifies two distinct phases in correspondence matching: an early transient phase and a sustained phase.
- Perceptual stability is maintained over time once established.
- Visual perception of depth from stereoscopic stimuli involves dynamic, phase-dependent processes.
Related Concept Videos
01:23Stability of Equilibrium Configuration
Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
01:13Stability of Equilibrium Configuration: Problem Solving
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
Problem-solving in the context of the stability of equilibrium configuration...
01:14Stability of structures
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
01:24BIBO stability of continuous and discrete -time systems
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
01:24Pole and System Stability
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's response.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's response.
01:28Stability
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...