Running Interactive Perception Applications on Open Cirrus

Abstract

Interactive perception applications, such as gesture recognition and vision-based user interfaces, process high-data rate streams with compute intensive computer vision and machine learning algorithms. Yet, they require extremely low latencies to remain interactive and ensure timely results to users. Cluster computing resources, such as those provided by Open Cirrus deployments, can help address the computation requirements, but significant challenges exist in practice. This paper highlights our efforts to parallelize interactive perception applications, tune them for best fidelity and latency, and place, schedule, and execute them on a cluster platform. We also look at remaining open problems and potential solutions.