Model-Based Vision System by Object-Oriented Programming

This paper presents an approach to using object-oriented programming for the generation of a object recognition program that recognizes a complex 3-D object within a jumbled pile. We generate a recognition program from an interpretation tree that classifies an object into an appropriate attitude group, which has a similar appearance. Each node of an interpretation tree represents a feature matching. We convert each feature extracting or matching operation into an individual processing entity, called an object. Two kinds of objects have been prepared data objects and event objects. A data object is used for representing geometric objects such as edges and regions and extracting features from geometric objects. An event object is used for feature matching and attitude determination. A library of prototypical objects is prepared and an executable program is constructed by properly selecting and instantiating modules from it. The object-oriented programming paradigm provides modularity and extensibility. This method has been applied to the generation of a recognition program for a toy wagon. The generated program has been tested with real scenes and has recognized the wagon in a pile. Keywords Robotics Libraries.