Content enrichment for mobile context aware imaging applications with a social aspect
Bibliographic record
Abstract
With technological advancements in data collection techniques allowing increasing amounts of contextual metadata to be appended to everyday image files, it has become a daunting task to effectively display such supplemental data alongside original image content without overloading users with information.I propose a unique approach to actively display geo-tagged image content that embeds the images in a navigable 3D environment in a way that makes explicit the geographical context and spatiotemporal relationships between the images.This approach enhances the viewer's comprehension of the image's context and content thus supporting my hypothesis that context extracted from metadata can enhance image content absorption rather than hinder it.The 3D environment is built by mapping Google Street View images onto a spherical tessellation within which user image content is overlaid.The proposed geographical browser and social-networking system is implemented on an iPad, using the iPad's built-in compass, gyroscopes, and accelerometers to provide real-time gesture control and spatial orientation.User studies were performed on the proposed system as well as on a standard social-networking application for comparison purposes.The results were used to evaluate the relative performance of the system in enabling users to absorb and comprehend image information.Test subject were found to consistently answer questions more accurately on images viewed on the proposed system as compared to the images viewed on a typical social-networking application.iii AbstraitLes avances technologiques dans les techniques de collection de donnes augmentant la quantit de mta donnes contextuelles associer aux images de tous les jours, afficher ces donnes supplmentaires de manire effective avec l'image originale est devenu une tche ardue.Je propose une approche unique permettant d'afficher de manire active du contenu go taggu qui renferme des images dans un environnement 3D navigable d'une manire qui rend explicite le contexte gographique et la relation spatiotemporelle entre les images.Cette approche augmente la comprhension du contexte et du contenu de l'image par l'observateur, supportant ainsi ma thse selon laquelle le contexte extrait des mtadonnes peut amliorer l'absorption du contenu de l'image plutt que de le cacher.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".