An Hypothesis-Driven Recognition System for the Blocks World

Abstract

This paper presents a visual recognition program in which recognition process is driven by hypotheses about the object being recognized. The hypothesis suggests which features to examine next, refines its predictions based on observed information, and selects a new hypothesis when observations contradict its predictions. After presenting the program, the paper identifies and discusses a number of theoretical issues raised by this work.