High dynamic range (HDR) video image processing for digital glass
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present highly parallelizable and computationally efficient High Dynamic Range (HDR) image compositing, reconstruction, and spatotonal mapping algorithms for processing HDR video. We implemented our algorithms in the EyeTap Digital Glass electric seeing aid, for use in everyday life. We also tested the algorithms in extreme dynamic range situations, such as, electric arc welding. Our system runs in real-time, and requires no user intervention, and no fine-tuning of parameters after a one-time calibration, even under a wide variety of very difficult lighting conditions (e.g. electric arc welding, including detailed inspection of the arc, weld puddle, and shielding gas in TIG welding). Our approach can render video at 1920x1080 pixel resolution at interactive frame rates that vary from 24 to 60 frames per second with GPU acceleration. We also implemented our system on FPGAs (Field Programmable Gate Arrays) for being miniaturized and built into eyeglass frames.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it