Spatial Aggregation: Language and Applications

Abstract

Spatial aggregation is a framework for organizing com-putations around image-like, analogue representations of physical processes in data interpretation and control tasks. It conceptualizes common computational struc-tures in a class of implemented problem solvers for dif-ficult scientific and engineering problems. It comprises a mechanism, a language, and a programming style. The spatial aggregation mechanism transforms a nu-merical input field to successively higher-level descrip-tions by applying a small, identical set of operators to each layer given a metric, neighborhood relation and equivalence relation. This paper describes the spatial aggregation language and its applications. The spatial aggregation language provides two ab-stract data types- neighborhood graph and field-and a set of interface operators for constructing the transformations of the field, together with a library of component implementations from which a user can mix-and-match and specialize for a particular applica-tion. The language allows users to isolate and express important computational ideas in different problem domains while hiding low-level details. We illustrate the use of the language with examples ranging from trajectory grouping in dynamics interpretation to re-gion growing in image analysis. Programs for these different task domains can be written in a modular, concise fashion in the spatial aggregation language.