Computer vision is a complex field which can be challenging for those outside the community to apply in the real world. In this paper we show how to provide access to sophisticated computer vision methods to general developers, hobbyists or researchers outside the field. Our contribution is an abstraction used to describe images, local image conditions and between-image conditions using segments as a basis. We illustrate how a descriptive language model can be built on the segment to provide an intuitive mental model of computer vision to mainstream developers. We then demonstrate how we can map a description of the task composed of the segment-based language into the space of algorithms in order to choose an appropriate method to solve the problem. We use the problems of segmentation, correspondence and image registration to show how end-to-end problems may be constructed using our novel metaphor.

Presented in Regina, May 2013 at the International Conference on Computer and Robot Vision.