Properties and Applications of Shape Recipes

In low-level vision, the representation of scene properties such as shape, albedo, etc., are very high dimensional as they have to describe complicated structures. The approach proposed here is to let the image itself bear as much of the representational burden as possible. In many situations, scene and image are closely related and it is possible to find a functional relationship between them. The scene information can be represented in reference to the image where the functional specifies how to translate the image into the associated scene. We illustrate the use of this representation for encoding shape information. We show how this representation has appealing properties such as locality and slow variation across space and scale. These properties provide a way of improving shape estimates coming from other sources of information like stereo.

Implementing Universal Computation in an Evolutionary System

Evolutionary algorithms are a common tool in engineering and in the study of natural evolution. Here we take their use in a new direction by showing how they can be made to implement a universal computer. We consider populations of individuals with genes whose values are the variables of interest. By allowing them to interact with one another in a specified environment with limited resources, we demonstrate the ability to construct any arbitrary logic circuit. We explore models based on the limits of small and large populations, and show examples of such a system in action, implementing a simple logic circuit.