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Record W1980841370 · doi:10.1117/12.705607

A framework for MPEG-21 DIA based adaptation and perceptual encryption of H.264 video

2007· article· en· W1980841370 on OpenAlexaff
Razib Iqbal, Shervin Shirmohammadi, Abdulmotaleb El Saddik

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Steganography and Watermarking Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceEncryptionAdaptation (eye)PersonalizationMultimediaOverhead (engineering)Content adaptationComputer networkEmbedded systemComputer architectureUbiquitous computingHuman–computer interactionOperating systemWorld Wide Web

Abstract

fetched live from OpenAlex

A ubiquitous computing concept permits end users to have access to multimedia and digital content anywhere, anytime and in any way they want. As a consequence, the importance of resource customization according to user preferences and device requirements set the primary challenge towards seamless access. Moreover, once a suitable customization approach has been decided (e.g. adaptation), deploying it in the existing network requires a generic and widely accepted standard applied to the process. With the advancement of time, performing encryption in the compressed domain should also be taken care of not only for serving sensitive digital contents but also for offering security as an embedded feature of the adaptation practice to ensure digital right management and confidentiality. In this paper, we present an architecture for temporal adaptation of ITU-T H.264 video conforming to ISO/IEC MPEG-21 DIA. In addition, we present a perceptual encryption scheme that is integrated in the system for video encryption. The framework enables video bitstreams to be adapted and encrypted in the compressed domain, eliminating cascaded adaptation (i.e. decoding - adaptation - encoding). The encryption framework is applied on the adapted video content, which reduces computational overhead compared to that on the original content. A prototype, based on the proposed architecture and experimental evaluations of the system as well as its performance supporting the architecture are also presented.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.621
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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 designBench or experimental
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

Citations12
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Steganography and Watermarking TechniquesFrench-language works237,207