Visual Perception - The Cognitive and Computational Approaches

The Cognitive and Computational Approaches

The major problem with the Gestalt laws (and the Gestalt school generally) is that they are descriptive not explanatory. For example, one cannot explain how humans see continuous contours by simply stating that the brain "prefers good continuity". Computational models of vision have had more success in explaining visual phenomena and have largely superseded Gestalt theory. More recently, the computational models of visual perception have been developed for Virtual Reality systems—these are closer to real life situation as they account for motion and activities which are prevalent in the real world. Regarding Gestalt influence on the study of visual perception, Bruce, Green & Georgeson conclude:

The physiological theory of the Gestaltists has fallen by the wayside, leaving us with a set of descriptive principles, but without a model of perceptual processing. Indeed, some of their "laws" of perceptual organisation today sound vague and inadequate. What is meant by a "good" or "simple" shape, for example?

In the 1970s David Marr developed a multi-level theory of vision, which analysed the process of vision at different levels of abstraction. In order to focus on the understanding of specific problems in vision, he identified three levels of analysis: the computational, algorithmic and implementational levels. Many vision scientists, including Tomaso Poggio, have embraced these levels of analysis and employed them to further characterize vision from a computational perspective.

The computational level addresses, at a high level of abstraction, the problems that the visual system must overcome. The algorithmic level attempts to identify the strategy that may be used to solve these problems. Finally, the implementational level attempts to explain how solutions to these problems are realized in neural circuitry.

Marr suggested that it is possible to investigate vision at any of these levels independently. Marr described vision as proceeding from a two-dimensional visual array (on the retina) to a three-dimensional description of the world as output. His stages of vision include:

• A 2D or primal sketch of the scene, based on feature extraction of fundamental components of the scene, including edges, regions, etc. Note the similarity in concept to a pencil sketch drawn quickly by an artist as an impression.
• A 2½ D sketch of the scene, where textures are acknowledged, etc. Note the similarity in concept to the stage in drawing where an artist highlights or shades areas of a scene, to provide depth.
• A 3 D model, where the scene is visualized in a continuous, 3-dimensional map.