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Record W2081772393 · doi:10.1145/2487276.2487281

Morphable guidelines for the human head

2013· article· en· W2081772393 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFace recognition and analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsImage warpingComputer scienceArtificial intelligenceComputer visionFace (sociological concept)Facial recognition systemHuman headHead (geology)Rotation (mathematics)Computer graphics (images)Feature extractionEngineering

Abstract

fetched live from OpenAlex

We present a system to help users achieve better face warping on 2D portrait images. Faces can be difficult to warp accurately because the rotation of the head affects the shape of the facial features. We bypass this problem by utilizing the Loomis 'ball and plane' head drawing method as a proxy structure. The resulting 'morphable guidelines' consist of a simple 3D head model. This proxy model can be reshaped by the user to mimic the positioning and proportions of a face in their input image. The vertices of the model act as deformation points for a 2D image deformation algorithm. Thus, the user can seamlessly transform the face proportions in the 2D image by transforming the proportions of the morphable guidelines. This technique can be used for both retouching and caricature warping purposes, as it is well-suited for both subtle and extreme modifications. Our system is advantageous over previous work in face warping because our morphable guidelines can be used on a wide range of head orientations and do not require the generation and reintegration of a full 3D model.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.846
Threshold uncertainty score0.694

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.140
GPT teacher head0.366
Teacher spread0.226 · 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

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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