# Strategy for Boosting Pair Comparison and Improving Quality Assessment Accuracy

arXiv: https://arxiv.org/abs/2010.00370 · HTML: https://mlsanity.com/paper/2010.00370/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2020.

## Built on by (most cited first, 5 of 5)

- [Subjective and Objective Quality Assessment of Mobile Gaming Video](https://mlsanity.com/paper/2103.05099/) (2021)
- [Active Preference Learning for Ordering Items In- and Out-of-sample](https://mlsanity.com/paper/2405.03059/) (2024)
- [Considering user agreement in learning to predict the aesthetic quality](https://mlsanity.com/paper/2110.06956/) (2021)
- [Improving Maximum Likelihood Difference Scaling method to measure inter content scale](https://mlsanity.com/paper/2203.13186/) (2022)
- [Towards Standardized Light Field Quality Assessment: Hybrid Subjective Benchmarking and Objective Metric Evaluation](https://mlsanity.com/paper/2607.03494/) (2026)

## Abstract (arXiv)

The development of rigorous quality assessment model relies on the collection of reliable subjective data, where the perceived quality of visual multimedia is rated by the human observers. Different subjective assessment protocols can be used according to the objectives, which determine the discriminability and accuracy of the subjective data. Single stimulus methodology, e.g., the Absolute Category Rating (ACR) has been widely adopted due to its simplicity and efficiency. However, Pair Comparison (PC) is of significant advantage over ACR in terms of discriminability. In addition, PC avoids the influence of observers' bias regarding their understanding of the quality scale. Nevertheless, full pair comparison is much more time-consuming. In this study, we therefore 1) employ a generic model to bridge the pair comparison data and ACR data, where the variance term could be recovered and the obtained information is more complete; 2) propose a fusion strategy to boost pair comparisons by utilizing the ACR results as initialization information; 3) develop a novel active batch sampling strategy based on Minimum Spanning Tree (MST) for PC. In such a way, the proposed methodology could achieve the same accuracy of pair comparison but with the compelxity as low as ACR. Extensive experimental results demonstrate the efficiency and accuracy of the proposed approach, which outperforms the state of the art approaches.