PIR: A Domain Specific Language for Multimedia Retrieval

Abstract

Multimedia retrieval is a problem domain involving salient features extraction, machine learning, indexing, and retrieval. There are a variety of implementations for these tasks, which are difficult to compose and reuse due to the interface and language incompatibility. Because of this low reusability, researchers often have to implement their experiments from scratch and the resulting programs are not optimized for efficiency and cannot be easily adapted for parallelization. In this paper, we present PIR (Pipeline Information Retrieval), a domain specific language (DSL) for multimedia feature manipulation. The goal is to unify the programming tasks for feature-related programming in multimedia retrieval experiments by hiding the programming details under a flexible layer of domain specific interface. This DSL enables us to optimize the feature-related tasks by compiling the DSL programs into pipeline graphs, which can be executed using a variety of strategies to eliminate redundant computation and enable parallelization and change propagation.