HEMVIP: Human Evaluation of Multiple Videos in Parallel

TL;DR

HEMVIP is a new framework enabling efficient, parallel, and detailed subjective evaluation of multiple videos simultaneously, reducing resource requirements compared to traditional pairwise methods.

Contribution

This paper introduces HEMVIP, a novel framework for parallel, granular video evaluation, validated to produce results consistent with traditional pairwise comparison methods.

Findings

HEMVIP provides reliable evaluation results aligned with pairwise methods.

The framework reduces evaluation time and resource consumption.

Validation confirms the method's effectiveness for subjective video assessment.

Abstract

In many research areas, for example motion and gesture generation, objective measures alone do not provide an accurate impression of key stimulus traits such as perceived quality or appropriateness. The gold standard is instead to evaluate these aspects through user studies, especially subjective evaluations of video stimuli. Common evaluation paradigms either present individual stimuli to be scored on Likert-type scales, or ask users to compare and rate videos in a pairwise fashion. However, the time and resources required for such evaluations scale poorly as the number of conditions to be compared increases. Building on standards used for evaluating the quality of multimedia codecs, this paper instead introduces a framework for granular rating of multiple comparable videos in parallel. This methodology essentially analyses all condition pairs at once. Our contributions are 1) a proposed framework, called HEMVIP, for parallel and granular evaluation of multiple video stimuli and 2) a validation study confirming that results obtained using the tool are in close agreement with results of prior studies using conventional multiple pairwise comparisons.