Objective Video Quality Assessment
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.291 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Effective and efficient objective video quality assessment (VQA) methods are highly desirable in modern visual communication systems for performance evaluation, quality control and resource allocation purposes.Simple VQA algorithms may be developed by direct extensions of still image quality assessment (IQA) approaches on a frame-by-frame basis.Advanced VQA methods take into account the temporal correlation and motion information contained in video signals but often lead to significantly increased computational complexity.Here we use a different approach to examine a video signal by considering it as a three-dimensional (3D) volume image.Specifically, we propose a 3D structural similarity (3D-SSIM) approach, which first creates a 3D quality map by applying SSIM evaluations within local 3D blocks, and then use local information content and local distortion based weighting methods to pool the quality map into a single quality measure.The resulting 3D-SSIM algorithm is computationally efficient and demonstrates highly competitive performance in comparison with state-of-the-art VQA algorithms when tested using four publicly available video quality databases 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.
The record
- Venue
- Topic
- Image and Video Quality Assessment
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Keywords
- Quality assessmentQuality (philosophy)Computer scienceReliability engineeringEngineeringEvaluation methodsPhilosophyEpistemology
- Has abstract in OpenAlex
- yes