A Primitive Recognizer of Figures in a Scene

Abstract

Given a scene, as seen for instance from a T.V. camera or a picture, it is desired to analyze it to organize, differentiate and identify desired objects or classes of objects (i.e., patterns) in it. The present report describes a program, written in CONVERT, which partially achieves this goal. Two inputs to the program determine its behavior and response: 1. The scene to be analyzed, which is entered in a symbolic format (it may contain 3-dimensional and curved objects). 2. A symbolic description -- called the model -- of the class for the objects we want to identify in the scene (1): Given a set of models for the objects we want to locate, and a scene or picture, the program will identify in it all those objects or figures which are similar to one of the models, provided they appear complete in the picture (i.e., no partial occlusion or hidden parts). Recognition is independent of position, orientation, size etc.; it strongly depends on the topology of the model. Important restrictions and suppositions are: (a) the input is assumed perfect --noiseless-- and highly organized; (b) more than one mode is, in general, required for the description of one object and (c) only objects which appear unobstructed are recognized. Work is continuing in order to drop restriction (c) and to improve (a).