Degenerate Motions in Multicamera Cluster SLAM with Non-overlapping\n Fields of View
Bibliographic record
Abstract
An analysis of the relative motion and point feature model configurations\nleading to solution degeneracy is presented, for the case of a Simultaneous\nLocalization and Mapping system using multicamera clusters with non-overlapping\nfields-of-view. The SLAM optimization system seeks to minimize image space\nreprojection error and is formulated for a cluster containing any number of\ncomponent cameras, observing any number of point features over two keyframes.\nThe measurement Jacobian is transformed to expose a reduced-dimension\nrepresentation such that the degeneracy of the system can be determined by the\nrank of a dense submatrix. A set of relative motions sufficient for degeneracy\nare identified for certain cluster configurations, independent of target model\ngeometry. Furthermore, it is shown that increasing the number of cameras within\nthe cluster and observing features across different cameras over the two\nkeyframes reduces the size of the degenerate motion sets significantly.\n
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".