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Record W7096344025

R&D status of ERIC-7 and MADIS: two systems for MPEG-7 indexing/search of audio-visual content

2005· article· en· W7096344025 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Analysis and Summarization
Canadian institutionsnot available
Fundersnot available
KeywordsSearch engine indexingXMLSchema (genetic algorithms)Encoding (memory)ModalitiesInterface (matter)Visualization
DOInot available

Abstract

fetched live from OpenAlex

We present the research and development status of two MPEG-7 indexing/search systems under development at the Computer Research Institute of Montreal (CRIM). The first (called ERIC-7) targets content-based encoding of still images and is mainly designed to experiment with the various aspects of the visual MPEG-7/XML schema with the help of analysis and exploration tools. The interface allows navigating graphically among the various descriptors in the XML files and through interactive UML graphics. The second (called MADIS) aims at providing a practical audiovisual MPEG-7 indexing/retrieval tool, within the framework of a light architecture. MADIS is designed to (1) be fully MPEG-7 compliant, (2) address both encoding and search, (3) combine audio, speech and visual modalities and (4) have search capability on the Internet. MADIS currently targets content-based indexing of documentary films. Keywords: MPEG-7, video processing, multimedia systems, content-based image retrieval, audio-visual indexing 1.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.307

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)0.0000.000

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 head0.084
GPT teacher head0.331
Teacher spread0.247 · 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 designSimulation or modeling
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

Citations0
Published2005
Admission routes1
Has abstractyes

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