Evidence that Viewers Prefer Higher Frame-Rate Film
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
High frame-rate (HFR) movie-making refers to the capture and projection of movies at frame rates several times higher than the traditional 24 frames per second. This higher frame rate theoretically improves the quality of motion portrayed in movies, and helps avoid motion blur, judder, and other undesirable artifacts. However, there is considerable debate in the cinema industry regarding the acceptance of HFR content given anecdotal reports of hyper-realistic imagery that reveals too much set and costume detail. Despite the potential theoretical advantages, there has been little empirical investigation of the impact of high frame-rate techniques on the viewer experience. In this study, we use stereoscopic 3D content, filmed and projected at multiple frame rates (24, 48, and 60 fps), with shutter angles ranging from 180° to 358°, to evaluate viewer preferences. In a paired-comparison paradigm, we assessed preferences along a set of five attributes (realism, motion smoothness, blur/clarity, quality of depth, and overall preference). The resulting data show a clear preference for higher frame rates, particularly when contrasting 24 fps with 48 or 60 fps. We found little impact of shutter angle on viewers' choices, with the exception of one measure (motion smoothness) for one clip type. These data are the first empirical evidence of the advantages afforded by high frame-rate capture and presentation in a cinema context.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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