adder-viz: Real-Time Visualization Software for Transcoding Event Video
This is an incremental improvement for researchers working with neuromorphic event video in computer vision applications.
The paper introduces improvements to adder-viz software for real-time visualization of event video transcoding, addressing limitations in flexibility, speed, and compressibility of existing representations.
Recent years have brought about a surge in neuromorphic ``event'' video research, primarily targeting computer vision applications. Event video eschews video frames in favor of asynchronous, per-pixel intensity samples. While much work has focused on a handful of representations for specific event cameras, these representations have shown limitations in flexibility, speed, and compressibility. We previously proposed the unified ADDER representation to address these concerns. This paper introduces numerous improvements to the adder-viz software for visualizing real-time event transcode processes and applications in-the-loop. The MIT-licensed software is available from a centralized repository at https://github.com/ac-freeman/adder-codec-rs.