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Record W4254367521 · doi:10.1109/cvpr.2009.5204340

Synchronization and rolling shutter compensation for consumer video camera arrays

2009· article· en· W4254367521 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · 2009
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsShutterSubframeComputer scienceSynchronization (alternating current)Rolling shutterComputer visionComputer graphics (images)Compensation (psychology)Artificial intelligenceMotion compensationComputer hardwareReal-time computingTelecommunicationsOpticsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Two major obstacles to the use of consumer camcorders in computer vision applications are the lack of synchronization hardware, and the use of a "rolling" shutter, which introduces a temporal shear in the video volume. We present two simple approaches for solving both the rolling shutter shear and the synchronization problem at the same time. The first approach is based on strobe illumination, while the second employs a subframe warp along optical flow vectors. In our experiments we have used the proposed methods to effectively remove temporal shear, and synchronize up to 16 consumer-grade camcorders in multiple geometric configurations.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.284
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it