adder-viz: Real-Time Visualization Software for Transcoding Event Video
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909752650366976 |
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| author | Freeman, Andrew C. Reinkensmeyer, Luke |
| author_facet | Freeman, Andrew C. Reinkensmeyer, Luke |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_14996 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | adder-viz: Real-Time Visualization Software for Transcoding Event Video Freeman, Andrew C. Reinkensmeyer, Luke Multimedia Computer Vision and Pattern Recognition Human-Computer Interaction Image and Video Processing 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. |
| title | adder-viz: Real-Time Visualization Software for Transcoding Event Video |
| topic | Multimedia Computer Vision and Pattern Recognition Human-Computer Interaction Image and Video Processing |
| url | https://arxiv.org/abs/2508.14996 |