FocalVid: A Platform for Tracking Visual Attention to Video via Crowdsourcing Validated Against Human Gaze Data
Bibliographic record
Abstract
Human attention to dynamic visual stimuli can be measured using mouse-contingent cursor movements as a proxy for tracking human gaze when eye tracking is not feasible, for example, in online studies. FocalVid is the first such platform for collecting mouse-contingent attention data for video as a proxy approximating eye tracking. The present study analyses in detail how data collected with FocalVid are related to human gaze data. Cursor movements of 225 participants watching a variety of videos are compared to eye movements for an established corpus on human gaze that used the same videos. Such a comparison is critical to justifying the use of FocalVid or similar platforms, and for choosing suitable user interface settings to produce results most similar to human gaze. Cursor movements in FocalVid are shown to have notable similarities with eye movements. For example, distributions of cursor velocities and fixation durations are qualitatively similar to those of eye movements. However, moment-to-moment cursor movements and eye movements were significantly different with most video stimuli. We discuss the implications for mouse-contingent attention measures to video stimuli in different contexts.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".