Gestalt Features for Biological and Computational Vision

The Problem: The goal of of the visual system, computer or biological, is to transform a visual input into meaningful semantic information. The three major factors controlling this computation are the architecture, representation, and learning algorithm. The architecture defines the structure of the process, whether completely feed-forward, whether objects are completely independent or rely upon shared components, etc. The representation defines how the information is represented mathematically. This can be either as simple as a list of gray values, or much more complicated. And finally the learning algorithm defines both how the algorithm parameters are set, and how meanings are gleaned from test data. This project involves the second part, the representation. Specifically, we will explore how we can use influences from the Gestalt psychologists in developing representations which are conducive to more accurate image understanding and better models of human biology. We will develop computational methods for discovering gestalt principles like good continuity, closed forms, parallelism and symmetry. Motivation:.It has been shown that image representation can be critical to the success of an image under- standing system, be it involving object detection, face recognition, or otherwise. Furthermore, our lab has had success in modeling mammalian visual systems, and then using the model in a compute