Plato's Cave: The Lighted Bubble Model

The Lighted Bubble Model

You will recall that in the [Bubble Model] the input image is projected on the front face of a block of perceptual tissue from whence it stimulates the percept of surfaces in depth within the volume of the block by inverse projection. The perceived surface is represented by a change in state of the elements of the block from transparent to opaque, at a depth corresponding to the depth of the perceived surface.

In the lighted bubble model each element of the block encodes three values; one for the perceived brightness, b of the surface, one for the underlying "lightness" l or reflectance of the surface, and one for the perceived strength of illumination i of that surface. The perceived brightness is copied directly from the input image on to the surface, where it is factored into lightness and illumination by the formula

                    b = l x i

in other words, the brighter the supposed illumination strength, the darker the surface reflectance must be to account for the perceived brightness, and vice-versa. This relationship can be encoded dynamically by three "nodes" representing the three values; node b copies its value directly from the input image, and sends activation to both nodes l and i in proportion to its own activation. Nodes l and i have a mutually inhibitory connection, so the stronger the activation of one of them, the more it weakens the other. This circuit encodes the factorization of brightness into lightness and illuminance for every point on the perceived surface.

The illuminance value of a surface gives information about the strength and direction of the illumination source- the brighter the source, and the more normal its direction of illumination to the surface, the greater the illumination of that surface. This information can therefore be "projected backwards" as a hypothesis of the illumination source, using the "texture of collinearity connections" by providing a "cosine gating" between the illuminance node i and all collinearity lines passing through that point, i.e. the activation value of node i is projected backwards at full strength in a direction normal to the perceived surface, and at the reduced strength of i cos(theta) at angles theta deviating from normal.

Each point on the surface of the perceptual sphere would summate all of the cosine gated illuminances from all surfaces projected backwards in the direction represented by that point. The surface of the perceptual sphere would thereby reflect an approximation of the illumination profile of the perceived scene. If many surfaces exhibit a bright "sunny side" in a certain direction, this would be reflected as a bright cosine function on the surface of the sphere, centered at that direction.

The illuminance strength on the surface of the perceptual sphere in turn is projected backwards to all opaque surfaces in the whole representation to impinge on those surfaces again through a cosine-gated connection, so that an illuminant from a certain direction would light up surfaces facing that direction in a manner that mimmicks the physics of light falling on a surface. This illuminant signal is communicated again to the local illuminance node i at every point in every perceived surface. This feedback connection expresses the relation that if most surfaces facing a certain direction reflect strong illumination, that suggests a strong illumination source in that direction. Conversely, if there is a strong illumination source in a certain direction, then all surfaces facing that direction would be expected to have a high illumination value. If a surface facing in that direction exhibits a low brightness, then this is likely due to a low reflectance of that surface, rather than low illuminance. This latter statement is embodied in the competitive relationship between nodes l and i, because l would be held at a high value due to the feedback from the "illumination source", which combined with a low value of the perceived brightness b would result in a low value for the lightness node l.

One more interaction is required to complete the model, and that is the tendency (in the absence of contradictory information) for objects to be perceived as having uniform lightness. This relation is expressed by the diffusion of lightness signal across perceived surfaces, so that a lightness value at one point on the surface will tend to equalize to the lightness value of neighboring points, except when separated by a perceived lightness edge. A visible edge in an image that is perceived as a form edge therefore would not restrict this diffusion of lightness, and thereby would attempt to account for any brightness difference across that edge by a difference in illuminance across that edge. This diffusion of lightness information corresponds to the diffusion of brightness in Grossberg's [Feature Contour System] model.

Return to argument

Return to Steve Lehar