A Real Time Augmented Reality System Using GPU Acceleration
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
Augmented Reality (AR) is an application of computer vision that is processor intensive and typically suffers from a trade-off between robust view alignment and real time performance. Real time AR that can function robustly in variable environments is a process difficult to achieve on a PC (personal computer) let alone on the mobile devices that will likely be where AR is adopted as a consumer application. Despite the availability of high quality feature matching algorithms such as SIFT, SURF and robust pose estimation algorithms such as EPNP, practical AR systems today rely on older methods such as Harris/KLT corners and template matching for performance reasons. SIFT-like algorithms are typically used only to initialize tracking by these methods. We demonstrate a practical system with real ime performance using only SURF without the need for tracking. We achieve this with extensive use of the Graphics Processing Unit (GPU) now prevalent in PC's. Due to mobile devices becoming equipped with GPU's we believe that this architecture will lead to practical robust AR.
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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 | 0.000 |
| Open science | 0.000 | 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