Abstract
This paper addresses the problem of grouping image primitives; its principal contribution is an explicit definition of the Gestalt principle of Pragnanz, which organizes primitives into descriptions of images that are both simple and stable. Our definition of Pragnanz assumes just two things: that a vector of free variables controls some general grouping algorithm, and a scalar function measures the information in a grouping. Stable descriptions exist where the gradient of the function is zero, and these can be ordered by information content (simplicity) to create a "grouping" or "Gestalt" scale description. We provide a simple measure for information in a grouping based on its structure alone, leaving our grouper free to exploit other Gestalt principles as we see fit. We demonstrate the value of our definition of Pragnanz on several real-world images.