Demo Data from VLDB 2026 / reviewers in the wild / expert
P. Matthew Bronstad
dblp:95/8374
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-3116-9322ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Multimedia systems and quality of experience · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia systems and quality of experience › video quality assessment
subjective video quality assessment |
0.2 | 1 | 2013 | Factors Affecting Enhanced Video Quality Preferences · IEEE Trans. Image Process. 2013 |
Multimedia systems and quality of experience
video quality assessment |
0.2 | 1 | 2013 | Factors Affecting Enhanced Video Quality Preferences · IEEE Trans. Image Process. 2013 |
Methods — techniques the papers use, named apart from their topics
paired comparison · 0.2binary logistic regression · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Erratum to "Factors Affecting Enhanced Video Quality Preferences"abstractIn the above paper (ibid., vol. 22, no. 12, pp. 5146-5157, Dec. 2013), a delay in communicating proof errors occurred. The paper was published without corrections. The corrections presented here are important. PremNandhini Satgunam, Russell L. Woods, P. Matthew Bronstad, Eli Peli |
IEEE Trans. Image Process. | 3 |
| 2013 | Factors Affecting Enhanced Video Quality PreferencesabstractThe development of video quality metrics requires methods for measuring perceived video quality. Most of these metrics are designed and tested using databases of images degraded by compression and scored using opinion ratings. We studied video quality preferences for enhanced images of normally-sighted participants using the method of paired comparisons with a thorough statistical analysis. Participants (n=40) made pair-wise comparisons of high definition video clips enhanced at four different levels using a commercially available enhancement device. Perceptual scales were computed with binary logistic regression to estimate preferences for each level and to provide statistical inference of the differences among levels and the impact of other variables. While moderate preference for enhanced videos was found, two unexpected effects were also uncovered: 1) participants could be broadly classified into two groups: a) those who preferred enhancement ("Sharp") and b) those who disliked enhancement ("Smooth") and 2) enhancement preferences depended on video content, particularly for human faces to be enhanced less. The results suggest that algorithms to evaluate image quality (at least for enhancement) may need to be adjusted or applied differentially based on video content and viewer preferences. The possible impact of similar effects on image quality of compressed video needs to be evaluated. PremNandhini Satgunam, Russell L. Woods, P. Matthew Bronstad, Eli Peli |
IEEE Trans. Image Process. | 3 |