The ADΔER Framework: Tools for Event Video Representations

The concept of "video" is synonymous with frame-sequence image representations. However, neuromorphic "event" cameras, which are rapidly gaining adoption for computer vision tasks, record frameless video. We believe that these different paradigms of video capture can each benefit from the lessons of the other. To usher in the next era of video systems and accommodate new event camera designs, we argue that we will need an asynchronous, source-agnostic processing pipeline. In this paper, we propose an end-to-end framework for frameless video, and we describe its modularity and amenability to compression and both existing and future applications.