Great thinking here!
I'd also point out the work Rafal and others have done over the past 3-5 years on motion quality metrics. Effectively in a series of papers, his team has improved the state of the art in motion quality metrics. To follow this motion quality metric work, start with his latest paper below and follow its references to the other metrics (linked for convenience below).
A contrast sensitivity function, or CSF, is a cornerstone of many visual models. It explains whether a contrast pattern is visible to the human eye. The existing CSFs typically account for a subset of relevant dimensions describing a stimulus, limiting the use of such functions to either static or foveal content but not both. In this paper, we propose a unified CSF, stelaCSF, which accounts for all major dimensions of the stimulus: spatial and temporal frequency, eccentricity, luminance, and area. To model the 5- dimensional space of contrast sensitivity, we combined data from 11 papers, each of which studied a subset of this space. While previously proposed CSFs were fitted to a single dataset, stelaCSF can predict the data from all these studies using the same set of parameters. The predictions are accurate in the entire domain, including low frequencies. In addition, stelaCSF relies on psychophysical models and experimental evidence to explain the major interactions between the 5 dimensions of the CSF. We demonstrate the utility of our new CSF in a flicker detection metric and in foveated rendering.
https://www.cl.cam.ac.uk/research/rainb ... /stelaCSF/
Content-adaptive Metric of Judder, Aliasing and Blur (CaMoJAB)
https://www.cl.cam.ac.uk/research/rainb ... h_Rate.pdf
FovVideoVDP is a video difference metric that models the spatial, temporal, and peripheral aspects of perception. While many other metrics are available, our work provides the first practical treatment of these three central aspects of vision simultaneously.
https://www.cl.cam.ac.uk/research/rainb ... deoVDP.pdf
The FovVideoVDP paper above has a great section dedicated to explaining the different types of metrics for motion quality.
We need to try to unify the applied work that you and the community do to the work that Rafal and others in academia. One place to start is to map the applied language to the academic language. I will put something together for further refining here.