A NTSC-compatible compact representation for stereoscopic sequences
Bibliographic record
Abstract
This paper describes a new spectral compaction method for interlaced stereoscopic sequences which combines the stereo information into the spectral space of a single NTSC video channel. The method makes use of the variable spatial and stereoscopic resolution of the human visual system and relies upon the determination of an area of fixation. Spectral compaction is achieved by retaining only the high-frequency information associated with this area. A composite video signal is formed by combining the lowpass, highpass and chrominance components of both channels into the available spectral space by means of modulation and filtering operations. Compatibility of the composite video signal with the NTSC standard is ensured by using the same colour subcarrier for the chrominance components of one channel and a second subcarrier whose phase is inverted on alternate fields to place the chrominance components of the second channel into the Fukinuki holes. Good quality results are obtained with relatively simple separable FIR filters.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".