An Interactive Scalable Multimedia Streaming Scheme for VBR-Encoded Videos
Bibliographic record
Abstract
The standard frame sequence of an MPEG encoded video stream is suitable for normal playback. However, its inter-frame dependency makes it difficult to use it for interactive playback modes, such as play backward, jump or fast forward/backward. A scalable streaming system is required to serve videos to a large number of clients and it should share a single server stream among many clients. However, different interactive clients generally ask for different playback sequences. Hence, their streams cannot be grouped and served together by a single server stream. Therefore, as the frequency of interaction increases, an ordinary scalable streaming service becomes a non-scalable service. In this paper, we have proposed an improved proxy-based streaming scheme over the Internet. We have used video segmentation and hybrid temporal-data-partition scalable video encoding to create suitable playback sequence for interactive playback modes. We have used prefix and smoothing buffers at the proxy to make our scheme scalable. Simulation results show that our streaming scheme remains fully scalable even when all the clients are highly interactive. By using certain part of the available server-proxy network bandwidth and proxy buffers, our streaming scheme can support large numbers of clients. As the level of interaction increases the relative bandwidth and the buffer requirement decreases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".