Ztitch: A mobile phone application for immersive panorama creation, navigation, and social sharing
Bibliographic record
Abstract
This paper presents the design of Ztitch, a mobile phone application that can create immersive panoramic scenes in real time, where multiple photos are arranged in the 3D space according to their camera poses, maintaining a realistic perspective of the scene. By taking full advantage of the touchscreen, accelerometer, and gyroscope in the phone, Ztitch allows users to easily fine-tune each photo's position, navigate the scene, and edit the scenes created by others. When there is a undesired gap or overlap between the two ends of a 360° immersive panorama due to unknown camera focal length or accumulated errors, a fast and accurate algorithm is developed to jointly adjust the entire sequence to achieve the desired panorama. This is again achieved by leveraging the touchscreen of the phone. In addition, a fast color-balancing and exposure-compensation technique is developed to blend neighboring images.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".