OpenVX and Real-Time Certification: The Troublesome History

Abstract

Many computer-vision (CV) applications used in autonomous vehicles rely on historical results, which introduce cycles in processing graphs. However, existing response-time analysis breaks down in the presence of cycles, either by failing completely or by drastically sacrificing parallelism or CV accuracy. To address this situation, this paper presents a new graph-based task model, based on the recently ratified OpenVX standard, that includes historical requirements and their induced cycles as first-class concepts. Using this model, response-time bounds for graphs that may contain cycles are derived. These bounds expose a tradeoff between responsiveness and CV accuracy that hinges on the extent of allowed parallelism. This tradeoff is illustrated via a CV case study involving pedestrian tracking. In this case study, the methods proposed in this paper enabled significant improvements in both analytical and observed response times, with acceptable CV accuracy, compared to prior methods.