MétaCan
Menu
Back to cohort
Record W2290899229 · doi:10.14288/1.0064982

3D-TV Content generation and multi-view video coding

2010· article· en· W2290899229 on OpenAlexaff
Mahsa Talebpourazad

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceCoding (social sciences)Content (measure theory)MathematicsStatistics

Abstract

fetched live from OpenAlex

The success of the 3D technology and the speed at which it will penetrate the entertainment market will depend on how well the challenges faced by the 3D-broadcasting system are resolved. The three main 3D-broadcasting system components are 3D content generation, 3D video transmission and 3D display. One obvious challenge is the unavailability of a wide variety of 3D content. Thus, besides generating new 3D-format videos, it is equally important to convert existing 2D material to the 3D format. This is because the generation of new 3D content is highly demanding and in most cases, involves post-processing correction algorithms. Another major challenge is that of transmitting a huge amount of data. This problem becomes much more severe in the case of multiview video content. This thesis addresses three aspects of the 3D-broadcasting system challenges. Firstly, the problem of converting 2D acquired video to a 3D format is addressed. Two new and efficient methods were proposed, which exploit the existing relationship between the motion of objects and their distance from the camera, to estimate the depth map of the scene in real-time. These methods can be used at the transmitter and receiver-ends. It is especially advantageous to employ them at the receiver-end since they do not increase the transmission bandwidth requirements. Performance evaluations show that our methods outperform the other existing technique by providing better depth approximation and thus a better 3D visual effect. Secondly, we studied one of the problems caused by unsynchronized zooming in stereo-camera video acquisition. We developed an effective algorithm for correcting unsynchronized zoom in 3D videos. The proposed scheme finds corresponding pairs of pixels between the left and right views and the relationship between them. This relationship is used to estimate the amount of scaling and translation needed to align the views. Experimental results show our method produces videos with negligible scale difference and vertical parallax. Lastly, the transmission of 3D-content problem is addressed and two schemes for multiview video coding (MVC) are proposed. While both methods outperform the current MVC standard, one of them introduces significantly less random access delay compared to the MVC standard.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.977
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.211
Teacher spread0.184 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2010
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicAdvanced Vision and ImagingFrench-language works237,207