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Stereoscopic motion in depth

2011· book-chapter· en· W943248015 on OpenAlexaff
Robert S. Allison, Ian P. Howard

Bibliographic record

VenueCambridge University Press eBooks · 2011
Typebook-chapter
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
Fundersnot available
KeywordsStereoscopyMotion (physics)Computer visionGeologyComputer scienceComputer graphics (images)Artificial intelligenceGeography

Abstract

fetched live from OpenAlex

Introduction In 1997, we were designing experiments to assess the stability of correspondence between points in the two retinas and the phenomenon of stereoscopic hysteresis (Diner and Fender, 1987; Fender and Julesz, 1967). As part of these experiments, we presented binocularly uncorrelated random-dot images to the two eyes in a stereoscope. Binocularly uncorrelated images produce a percept of noisy, incoherent depth, since there is no consistent disparity signal. However, when we moved the images in the two eyes laterally in opposing directions we obtained a compelling sense of coherent motion in depth. When the display was stopped, the stimulus again appeared as noisy depth. We quickly realized that the motion-in-depth percept was consistent with dichoptic motion cues in the stimulus. Thus, a compelling sense of changing depth can be supported by a stimulus that produces no coherent static depth. This was quite surprising, since experiments several years earlier had suggested that stereoscopic motion-in-depth perception could be fully explained by changes in disparity between correlated images. Unknown to us, Shioiri and colleagues had made similar findings, which they reported at the same Association for Research in Vision and Opthalmology (ARVO) meeting where we first presented our findings (Shioiri et al ., 1998, 2000), although we found out they had also presented them earlier at a meeting in Japan. We performed a number of experiments on this phenomenon, reported as conference abstracts (Allison et al ., 1998; Howard et al ., 1998) that were subsequently cited.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.255
Teacher spread0.160 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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